Ravens Image: Steve Smith Sr. auctions off his cleats that were worn in Week 13 to support a domestic violence center (ESPN)

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[FD] CSRF vulnerability in Multisite Post Duplicator could allow an attacker to do almost anything an admin user can do (WordPress plugin)

Details ================ Software: Multisite Post Duplicator Version: 0.9.5.1 Homepage: http://ift.tt/2hgTOSc Advisory report: http://ift.tt/2gxUrrY CVE: Awaiting assignment CVSS: 5.8 (Medium; AV:N/AC:M/Au:N/C:P/I:P/A:N) Description ================ CSRF vulnerability in Multisite Post Duplicator could allow an attacker to do almost anything an admin user can do Vulnerability ================ Contains a CSRF vulnerability which can copy content from one site of a multisite installation to another. This could be used to add arbitrary HTML to the front-end of the site (which could be used for defacement, harvesting login credentials from authenticated users, or could be used to do virtually anything a logged-in admin user can do). This could also be used to view content not meant to be published. Proof of concept ================ Some of these values may need adjusting depending on the post IDs, blog IDs, etc.

Mitigations ================ Update to version 1.1.3 or later. Disclosure policy ================ dxw believes in responsible disclosure. Your attention is drawn to our disclosure policy: http://ift.tt/1B6NWzd Please contact us on security@dxw.com to acknowledge this report if you received it via a third party (for example, plugins@wordpress.org) as they generally cannot communicate with us on your behalf. This vulnerability will be published if we do not receive a response to this report with 14 days. Timeline ================ 2016-11-01: Discovered 2016-12-07: Tested version 1.1.3 and found the plugin no longer vulnerable to the attack as described 2016-12-09: Advisory published Discovered by dxw: ================ Tom Adams Please visit security.dxw.com for more information.

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Rumor Central: Free agent C Welington Castillo is Orioles' top target at position - BaltimoreBaseball.com; 68 RBI in '16 (ESPN)

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Can I make an anonymous polls and get a list of all participant names (without knowing who ...

I would like to administer a poll to some 150 students. I would like the entries to be anonymous, but I would like to have access to all the names of the ...

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Anonymous Leaks to the WashPost About the CIA's Russia Beliefs Are No Substitute for Evidence

There are many obvious reasons for skepticism about anonymous press leaks regarding Russia, but they are no match for partisan needs. We've seen ...

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8 Venetian Songs (Anonymous)

8 Venetian Songs (Anonymous). (Redirected from Canzoni veneziane (Anonymous)) ... Search key: anonymous venetian songs. change. (Top 10 ...

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Crime Coast: Mafia Wars (hack) Gold, Cash Generator -> mobile

Hi, this is Crime Coast: Mafia Wars Gold, Cash generator. Enter your username, choose the number of resource you want to generate.

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Anonymous

Anonymous. 5841607 likes · 334367 talking about this. We are Anonymous. Expect us. Our Podcast http://ift.tt/29k5gs3...

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New! Battle for the Throne cheat Runes Generator ~> online

Hi, this is Battle for the Throne Runes generator. Enter your username, choose the number of resource you want to generate.

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President Obama Orders 'Full Review' of Possible Russian hacking in US Election

In his final month in office, President Barack Obama has ordered U.S. intelligence agencies to conduct a "full review" of pre-election cyber attacks against Democratic Party organizations that many believe affected the outcome of the 2016 presidential election. The United States intelligence agencies have attributed those series of cyber-attacks to Russia that shook the US election season. "

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Stop Using these 2 Easily Hackable Netgear Router Models — US CERT Warns

Bad news for consumers with Netgear routers: Two popular Netgear routers are vulnerable to a critical security bug that could allow attackers to run malicious code with root privileges. Netgear's R7000 and R6400 routers, running current and latest versions of firmware, are vulnerable to arbitrary command injection attacks, though the number of users affected by the flaw is still unclear. <!--

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Anonymous Couple Brings Christmas Miracle To Gaston County Kids

GASTONIA, NC — $30,000 worth of toys will be going to the children of families who could not afford them in Gaston County thanks to a local couple.

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Assimilation of OCO-2 Carbon Dioxide into the GEOS Simulation

Carbon dioxide is the most important greenhouse gas released to the atmosphere through human activities. It is also influenced by natural exchange with the land and ocean. This visualization shows column-averaged atmospheric carbon dioxide concentrations from September 8, 2014 to August 31, 2015, every 3 hours. It was created using output from the GEOS modeling system, developed and maintained by scientists at NASA. Measurements of carbon dioxide from NASA's second Orbiting Carbon Observatory (OCO-2) spacecraft are incorporated into the model to update, or "correct," the model results, producing a realistic and high-resolution global picture of atmospheric carbon dioxide. This process of updating the model with real-world measurements is called data assimilation. In the beginning of the visualization, observations from the OCO-2 spacecraft (square data points) are overlaid on the model results. Typically the amount of carbon dioxide measured by OCO-2 is very close to the amount that the model predicts over a particular spot on Earth, though sometimes amounts are noticeably different. If you watch these spots closely, the next time the model is updated, you will notice that the amount of carbon dioxide the model predicts is closer to the amount previously observed by OCO-2. For decades, scientists have measured carbon dioxide at remote surface sites, but carbon dioxide is particularly difficult to measure from space because a very high degree of accuracy is needed to measure the gradients associated with emissions and weather systems. The OCO-2 mission has been designed to collect about a million high-precision, total column measurements of carbon dioxide (from the sensor to Earth's surface) each day, greatly increasing the number of observations available. While scientists learn a great deal from studying data from OCO-2 alone, numerical modeling and data assimilation capabilities allow them to combine different types of measurements (e.g., carbon dioxide and wind measurements) from various sources (e.g., satellites, aircraft, and ground-based observation sites) to study how carbon dioxide behaves in the atmosphere, where it is being emitted and removed from the atmosphere, and how much atmospheric carbon dioxide comes from natural processes and human activities. Studies like these that combine models and observations can help scientist make more realistic projections of how Earth's climate might respond to increases in carbon dioxide in the future. Carbon dioxide variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and orange shades represent regions where carbon dioxide concentrations are enhanced by carbon sources. During Northern Hemisphere fall and winter, when trees and plants begin to lose their leaves and decay, carbon dioxide is released in the atmosphere. This, combined with fewer trees and plants removing carbon dioxide from the atmosphere, allows concentrations to climb all winter, reaching a peak by early spring. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of carbon dioxide through photosynthesis, thus removing it from the atmosphere. While seasonal variations are most noticeable in this visualization, it is important to note that fossil fuel combustion and other human activities continue to increase the atmospheric carbon dioxide abundance to unprecedented levels--raising concerns about greenhouse-gas-induced climate change.

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I have a new follower on Twitter

Kristin Taylor
Growing companies call on me to create & run rock star marketing programs that kickstart and supercharge their sales. Love Portland and Illini. #OnCallMarketing
Portland & Vancouver USA
https://t.co/6ANsMOMlJb
Following: 10479 - Followers: 12275

December 09, 2016 at 11:49PM via Twitter http://twitter.com/xKristinTaylorx

Secret founder returns to anonymous publishing with launch of IO

Byttow launched the revived anonymous publishing app as IO on Thursday morning, with a different approach that has more in common with Medium ...

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I have a new follower on Twitter

Coralogix
Coralogix helps software companies avoid getting lost in their log data by figuring out their production problems automatically
San Francisco, CA
https://t.co/uNE1Je1VLI
Following: 2530 - Followers: 1916

December 09, 2016 at 09:24PM via Twitter http://twitter.com/Coralogix

8 Venetian Songs (Anonymous)

8 Venetian Songs (Anonymous) ... Naxos Search. Search key: anonymous venetian songs. change. (Top 10 results below) ...

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AP sources: Mattis received anonymous email in Petraeus case

WASHINGTON (AP) — The Associated Press has learned that President-elect Donald Trump's choice for defense secretary was among several ...

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Viagra Where To Really Anonymous

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Food Bank receiving $100K grant from anonymous donor

MANCHESTER, N.H. (AP) — The New Hampshire Food Bank has received a $100,000 matching grant from an anonymous donor that will help ...

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Tip-offs anonymous

... page Print this page; E-mail this page E-mail this page; Share this page Share this page. Currently viewing: Tip-offs anonymous / Next: PAIA manual ...

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Brothers who tortured boys to stay anonymous

Two brothers who were 10 and 11 when they tortured two young boys in South Yorkshire have been granted lifelong anonymity.

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Ravens Podcast: NFL Nation reporter Jamison Hensley breaks down matchup against Patriots and makes his Week 14 pick (ESPN)

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I have a new follower on Twitter

Stephane Bureau
International Marketing Executive coaching HPE partners with Cloud Solutions. Social Business, Visual Marketing, Entrepreneur, Photographer. Tweets are my own.
Grenoble, France _ EMEA

Following: 4369 - Followers: 4777

December 09, 2016 at 10:33AM via Twitter http://twitter.com/SBUCloud

I have a new follower on Twitter

FTP Today
File Share with FTP Today: Compatibility you need. Security you can trust. File sharing built to fit your business.
Cincinnati, OH
http://t.co/VgD9a5ln13
Following: 3625 - Followers: 3937

December 09, 2016 at 10:33AM via Twitter http://twitter.com/ftptoday

[FD] Broken access control on bluemix containers

# Date : 09/12/2016 # Author : Oscar Martinez # Tested on:cf version 6.22.1+6b7af9c-2016-09-24 / Docker version 1.12.3, build 6b644ec / API endpoint: http://ift.tt/QKImQk (API version: 2.54.0) API endpoint: http://ift.tt/QKImQk (API version: 2.54.0) # Vendor : IBM # Software : bluemix http://ift.tt/2cNOB18 # Vulnerability Description: It is assumed that a user with auditor role should not be able to create or delete containers. reference: http://ift.tt/2hmZbT8 But, a user with auditor role CAN create or delete containers using the cli CF. 1. Connect to bluemix using the cli CF with the user with "auditor" role. 1.1 cf login [-sso] 1.2 cf ic init 2. Show the images 2.1 cf ic images 3. Create the container 3.1 cf ic run --name broken_access_666 -p 8080 -m 512 http://ift.tt/2gIWYgT site]/[your image] example: cf ic run --name broken_access_666 -p 8080 -m 512 http://ift.tt/2hn0Ecf 4. Delete your container cf ic stop [your container] cf ic rm [your container] example: cf ic stop broken_access_666 cf ic rm broken_access_666 Time Line

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[FD] MSIE 9 MSHTML CElement::Has­Flag memory corruption

Since November I have been releasing details on all vulnerabilities I found that I have not released before. This is the twenty-ninth entry in the series. This information is available in more detail on my blog at http://ift.tt/2gkhCYk. There you can find a repro that triggered this issue in addition to the information below. If you find these releases useful, and would like to help me make time to continue releasing this kind of information, you can make a donation in bitcoin to 183yyxa9s1s1f7JBp­PHPmz­Q346y91Rx5DX. Follow me on http://twitter.com/berendjanwever for daily browser bugs. MSIE 9 MSHTML CElement::HasFlag memory corruption ================================================= (The fix and CVE number for this issue are not known) Synopsis

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This Ransomware Unlocks Your Files For Free If You Infect Others

Is your PC infected with Ransomware? Either pay the ransom amount to the attacker or spread the infection further to get the decryption keys. Yes, this new technique has been employed by cyber criminals with the latest round of ransomware threat, dubbed Popcorn Time. Initially discovered by MalwareHunterTeam, the new Popcorn Time Ransomware has been designed to give the victim's a criminal

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ISS Daily Summary Report – 12/08/2016

Everywear:  Today a crewmember configured the Smartshirt for exercise and then donned it for an exercise session with the Cycle Ergometer with Vibration Isolation and Stabilization (CEVIS) while data was recorded by the iPad Everywear application.  Everywear is an ambulatory data collection system that makes use of wearable sensors connected to an iPad tablet computer that is synchronized with ground computers. This easy-use system seeks to demonstrate the benefits of extensive physiology data collection for both science and medical follow-up purposes, by improving usability for crew members on the ISS. The main advantage of Everywear is the ability to aggregate data from different tools, but it also brings with it a simplification in procedures for astronauts. This is a versatile device that can cover a wide variety of needs with a tailored data collection capability that allows a unified treatment of data. The use of this personal assistant brings a very important gain in crew-time availability for ISS crew members.  Vascular Echo:  A crewmember performed a Vascular Echo resting ultrasound and blood pressure measurements this morning.  With assistance from a ground remote guidance team, he scanned his neck, thigh and heart. This Canadian Space Agency (CSA) investigation examines changes in blood vessels, and the heart, while the crew members are in space, and then follow their recovery on return to Earth. The results could provide insight into potential countermeasures to help maintain crew member health, and quality of life for everyone. Capillary Flow Experiment-2 (CFE-2): The crew set up and initiated test runs with the Interior Corner Flow 1 hardware in support of the CFE-2 Vane Gap experiment.  Because liquids behave differently in space than they do on Earth, containers that can process, hold or transport them must be designed to work in microgravity. The CFE-2 furthers research into the control of liquid behavior aboard spacecraft through wetting and container geometry. Vane Gap experiments identify the critical geometric wetting conditions of a vane structure that does not quite meet the container wall – a construct used in various fluid systems aboard spacecraft such as fuel tanks, thermal systems and water processors for life support.  The results of these tests may be used to improve the capability to quickly and accurately predict how related processes such as passive separation of gases from liquids in the absence of gravity occur.  Radiation Dosimetry Inside ISS-Neutron (RaDI-N):  After retrieving the RaDI-N hardware from the Russian crewmembers, a USOS crewmember deployed all 8 Space Bubble Detectors around the ISS for the Radi-N2 experiment. The Canadian Space Agency (CSA) RaDI-N investigation will be conducted by measuring neutron radiation levels while onboard the ISS. RaDI-N uses bubble detectors as neutron monitors which have been designed to only detect neutrons and ignore all other radiation.  Veg-03 Operations: The crew checked and photo-documented the status of the plants in the Veggie facility today.  The overall goal of Veg-03 is to further demonstrate proof-of concept for the Veggie plant growth chamber and the planting pillows using ‘Outredgeous’ Red Romaine lettuce.  Future long-duration missions into the solar system, will require a fresh food supply to supplement crew diets, which means growing crops in space. Previous investigations focused on improving productivity in controlled environments, but the limited quarters of the space shuttle and ISS made it difficult to conduct large-scale crop production tests. Veg-03 expands on previous validation tests of the new Veggie hardware, which crew members will soon use to grow cabbage, lettuce and other fresh vegetables in space. Tests determine which types of microorganisms are present in space-grown cabbage, providing baseline data for future crop-growing efforts.  Behavioral health surveys assess the impact of growing plants on crew morale and mood. Fluid System Servicer (FSS) Internal Thermal Control System (ITCS) Coolant Refill:  Earlier today the crew set up the FSS Fluids Control Pump Assembly (FCPA) and refilled the LAB Low Temperature Loop (LTL) Pump Package Assembly (PPA) accumulator.  Once filled, the crew relocated the FSS to the Columbus module and refilled the Columbus Water Pump Assembly (WPA) accumulator.  Then the FSS was used to fill the JEM ITCS Moderate Temperature Loop (MTL), followed by the filling of a pair of dry ITCS lines in Node 1/Node 3.  Port Solar Array Mast Imagery:  The crew completed a photo-survey of the port solar array masts by capturing a series of images from the Docking Compartment (DC)-1 Port window of the all four port mast structures from tip to base.  The ground is working on a plan to quantify and mitigate the risk of solar array mast structural failure due to Micro Meteoroid Orbital Debris (MMOD). Taking these images will provide an outstanding base configuration to compare MMOD strike probability against actuality. Port 1 Radiator Imagery:  The crew performed a routine survey of the P1 Radiator from the DC-1 Port window.  During the task the radiator was rotated to two different angles to photograph both sides of the Port Thermal Radiator Rotary Joint (TRRJ).  Today’s Planned Activities All activities were completed unless otherwise noted. EveryWear sleep assessment questionnaire filling Aerosol Samplers Battery Charge Photo/TV SAW MAST Setup Regenerative Environmental Control and Life Support System (RGN) WSTA Fill ALGOMETRIYA. Pressure and Thermal Mode Algometry preparation for and measurement session Crew empties lower compartment of COL1O2 in preparation for Columbus Fluid System Servicer (FSS) ops. Photo TV Camera Set Up For Radiator Inspection Fluid System Servicer (FSS) Setup and Refill in LAB Meteor Hard Drive Swapout СОЖ maintenance JPM1F0-01 CLOSEOUT PANEL FASTENER LOOSEN Un-powering the AstroPi Vis. EveryWear Smartshirt Gateway charging EveryWear Doffing of Biometric Patch and data transfer METEOR Grating Configuration OTKLIK. Hardware Monitoring Crew Medical Officer (CMO) On Board Training (OBT) Environmental Health System (EHS) Acoustic Dosimeter Operations – Setup Dosimeter for Static Measurement PhotoTV SAW Mast Port Survey EveryWear Biometric Patch close out activity PILOT-T. Preparation for the experiment. Tagup with specialists Ultrasound 2 HRF Rack 1 Power On Vascular Echo Resting Ultrasound Scan 135 Minutes – Subject Replacement of Chibis-M Removable Seal Curtain.  Get curtain No.2 URAGAN. Observation and Photography using […]

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Uber Now Tracks Your Location Even After Your Ride

Uber was in controversies at the mid of this year for monitoring the battery life of its users, as the company believed that its users were more likely to pay a much higher price to hire a cab when their phone's battery is close to dying. Uber is now tracking you even when your ride is over, and, according to the ride-hailing company, the surveillance will improve its service. Uber recently

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[FD] [ESNC-2041217] Critical Security Vulnerability in PwC ACE Software for SAP Security

*[ESNC-2041217] Critical Security Vulnerability in PwC ACE Software for SAP Security* Please refer to https://www.esnc.de for the original security advisory, updates, and additional information.

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[FD] Dual DHCP DNS Server 7.29 Buffer Overflow (Dos)

# Date : 07/12/2016 # Author : R-73eN # Tested on: Dual DHCP DNS Server 7.29 on Windows 7 SP1 (32bit) # Vendor : http://ift.tt/2haw5Tv # Software : http://ift.tt/2grwjqV # Vulnerability Description: # The software crashes when it tries to write to an invalid address. # # MOV EBX,DWORD PTR SS:[EBP+8] -> EBP+8 is part of our controlled input # MOV DWORD PTR SS:[ESP+4],31 # MOV DWORD PTR SS:[ESP],1 # ......................... # MOV DWORD PTR DS:[EBX+24],EAX -> Here happens the corruption, EAX fails to move EBX which is our controlled adress + 24 bytes. # # I think this vulnerability is not exploitable because every module that is loaded has ASLR/DEP/SAFESEH enabled (Win 7) # Even if we try to put some valid pointers to manipulate the execution flow we can't because every address on the DualServ.exe # contains 00 which is a badchar in our case. #

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[FD] Roundcube 1.2.2: Command Execution via Email

Roundcube 1.2.2: Command Execution via Email ============================================ You can find the online version of the advisory here: http://ift.tt/2hcmF9b Found by Robin Peraglie with RIPS Introduction

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[FD] Splunk Enterprise Server-Side Request Forgery

( , ) (, . '.' ) ('. ', ). , ('. ( ) ( (_,) .'), ) _ _, / _____/ / _ \ ____ ____ _____ \____ \==/ /_\ \ _/ ___\/ _ \ / \ / \/ | \\ \__( <_> ) Y Y \ /______ /\___|__ / \___ >____/|__|_| / \/ \/.-. \/ \/:wq (x.0) '=.|w|.=' _=''"''=. presents.. Splunk Enterprise Server-Side Request Forgery Affected versions: Splunk Enterprise <= 6.4.3 PDF: http://ift.tt/2hmoogm

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[FD] CVE-2013-1306: MSIE 9 MSHTML CDisp­Node::Insert­Sibling­Node use-after-free details

Since November I have been releasing details on all vulnerabilities I found that I have not released before. This is the twenty-eighth entry in the series. This information is available in more detail on my blog at http://ift.tt/2h6tCJS. There you can find a repro that triggered this issue in addition to the information below. Today's release is again not very interesting, because it also was one of the first bugs I found and reported back in 2012, before I had developed the tools and skills to properly analyze MSIE bugs. This report is therefore very scarce in information. I did get some more details from EIP about the root cause, which I've included. If you find this information useful, and would like to help me make time to continue releasing this kind of information, you can make a donation in bitcoin to 183yyxa9s1s1f7JBp­PHPmz­Q346y91Rx5DX. Follow me on http://twitter.com/berendjanwever for daily browser bugs. MSIE 9 MSHTML CDispNode::InsertSiblingNode use-after-free ========================================================= (MS13-037, CVE-2013-1306) Synopsis

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[FD] CVE-2013-1309:

Since November I have been releasing details on all vulnerabilities I found that I have not released before. This is the twenty-seventh entry in the series. This information is available in more detail on my blog at http://ift.tt/2hmj7W3. There you can find a repro that triggered this issue in addition to the information below. Today's release is not very interesting, because it was one of the first bugs I found and reported to the ZDI back in 2012, before I had developed the tools and skills to properly analyze MSIE bugs. This report is therefore very scarce in information. If you find this information useful, and would like to help me make time to continue releasing this kind of information, you can make a donation in bitcoin to 183yyxa9s1s1f7JBp­PHPmz­Q346y91Rx5DX. Follow me on http://twitter.com/berendjanwever for daily browser bugs. MSIE 9 MSHTML CDispNode::InsertSiblingNode use-after-free ========================================================= (MS13-037, CVE-2013-1309) Synopsis

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[FD] CVE-2015-1730: MSIE jscript9 Java­Script­Stack­Walker memory corruption details and PoC

Since November I have been releasing details on all vulnerabilities I found in web-browsers that I had not released before. I will try to continue to publish all my old vulnerabilities, including those not in web-browser, as long as I can find some time to do so. If you find this information useful, you can help me make more time available by donating bitcoin to 183yyxa9s1s1f7JBp­PHPmz­Q346y91Rx5DX. This is the twenty-sixth entry in the series. This information is available in more detail on my blog at http://ift.tt/2gLoBso. There you can find repros that triggered this issue in addition to a Proof-of-Concept exploit, as well as the information below. Today's release is interesting, in part because it is an odd vulnerability that I've not seen before or since: it's like a stack-based use-after-free. The time-line is also interesting in that ZDI first did not believe it to be exploitable and EIP thought it was a duplicate of a bug they had already reported to Microsoft. Both turned out to be wrong. Then I reported it to iDefense as well, who accidentally send the details over plain-text email, causing ZDI to reject my submission for fear of the bug leaking to the public. Luckily for me, iDefense did end up acquiring the bug. Follow me on http://twitter.com/berendjanwever for daily browser bugs. MSIE jscript9 JavaScriptStackWalker memory corruption ===================================================== (MS15-056, CVE-2015-1730) Synopsis

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Oversharers Anonymous

C'mon Everybody. 325 Franklin Avenue Brooklyn, NY, 11238. 8:00 PM. This event is 21 and over. Oversharers Anonymous ...

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Binary options anonymous

http://ift.tt/2h9RzQEanonymous CLICK HERE! Binary options anonymous. The entire process is fully ...

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I have a new follower on Twitter

you & your family
We educate expectant and new parents on pregnancy, fitness and nutrition, labor and birth and family and financial matters.

http://t.co/RVOpAu23sT
Following: 2725 - Followers: 2875

December 08, 2016 at 11:48PM via Twitter http://twitter.com/YouandYourFam

Anonymous Stranger Pays All Overdue Lunch Balances At Elementary School

The sign out side H W Good Elementary in the Yough School District reads "Happy Holidays," and something very happy happened here recently.

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Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. (arXiv:1612.02487v1 [cs.AI])

Providing accurate predictions is challenging for machine learning algorithms when the number of features is larger than the number of samples in the data. Prior knowledge can improve machine learning models by indicating relevant variables and parameter values. Yet, this prior knowledge is often tacit and only available from domain experts. We present a novel approach that uses interactive visualization to elicit the tacit prior knowledge and uses it to improve the accuracy of prediction models. The main component of our approach is a user model that models the domain expert's knowledge of the relevance of different features for a prediction task. In particular, based on the expert's earlier input, the user model guides the selection of the features on which to elicit user's knowledge next. The results of a controlled user study show that the user model significantly improves prior knowledge elicitation and prediction accuracy, when predicting the relative citation counts of scientific documents in a specific domain.

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Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning. (arXiv:1612.02516v1 [stat.ML])

We study the online estimation of the optimal policy of a Markov decision process (MDP). We propose a class of Stochastic Primal-Dual (SPD) methods which exploit the inherent minimax duality of Bellman equations. The SPD methods update a few coordinates of the value and policy estimates as a new state transition is observed. These methods use small storage and has low computational complexity per iteration. The SPD methods find an absolute-$\epsilon$-optimal policy, with high probability, using $\mathcal{O}\left(\frac{|\mathcal{S}|^4 |\mathcal{A}|^2\sigma^2 }{(1-\gamma)^6\epsilon^2} \right)$ iterations/samples for the infinite-horizon discounted-reward MDP and $\mathcal{O}\left(\frac{|\mathcal{S}|^4 |\mathcal{A}|^2H^6\sigma^2 }{\epsilon^2} \right)$ for the finite-horizon MDP.

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Prediction with a Short Memory. (arXiv:1612.02526v1 [cs.LG])

We consider the problem of predicting the next observation given a sequence of past observations. We show that for any distribution over observations, if the mutual information between past observations and future observations is upper bounded by $I$, then a simple Markov model over the most recent $I/\epsilon$ observations can obtain KL error $\epsilon$ with respect to the optimal predictor with access to the entire past. For a Hidden Markov Model with $n$ states, $I$ is bounded by $\log n$, a quantity that does not depend on the mixing time. We also demonstrate that the simple Markov model cannot really be improved upon: First, a window length of $I/\epsilon$ ($I/\epsilon^2$) is information-theoretically necessary for KL error ($\ell_1$ error). Second, the $d^{\Theta(I/\epsilon)}$ samples required to accurately estimate the Markov model when observations are drawn from an alphabet of size $d$ is in fact necessary for any computationally tractable algorithm, assuming the hardness of strongly refuting a certain class of CSPs.

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Inverses, Conditionals and Compositional Operators in Separative Valuation Algebra. (arXiv:1612.02587v1 [cs.AI])

Compositional models were introduce by Jirousek and Shenoy in the general framework of valuation-based systems. They based their theory on an axiomatic system of valuations involving not only the operations of combination and marginalisation, but also of removal. They claimed that this systems covers besides the classical case of discrete probability distributions, also the cases of Gaussian densities and belief functions, and many other systems.

Whereas their results on the compositional operator are correct, the axiomatic basis is not sufficient to cover the examples claimed above. We propose here a different axiomatic system of valuation algebras, which permits a rigorous mathematical theory of compositional operators in valuation-based systems and covers all the examples mentioned above. It extends the classical theory of inverses in semigroup theory and places thereby the present theory into its proper mathematical frame. Also this theory sheds light on the different structures of valuation-based systems, like regular algebras (represented by probability potentials), canncellative algebras (Gaussian potentials) and general separative algebras (density functions).

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Decision Theory in an Algebraic Setting. (arXiv:1612.02660v1 [cs.AI])

In decision theory an act is a function from a set of conditions to the set of real numbers. The set of conditions is a partition in some algebra of events. The expected value of an act can be calculated when a probability measure is given. We adopt an algebraic point of view by substituting the algebra of events with a finite distributive lattice and the probability measure with a lattice valuation. We introduce a partial order on acts that generalizes the dominance relation and show that the set of acts is a lattice with respect to this order. Finally we analyze some different kinds of comparison between acts, without supposing a common set of conditions for the acts to be compared.

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Fixpoint Approximation of Strategic Abilities under Imperfect Information. (arXiv:1612.02684v1 [cs.MA])

Model checking of strategic ability under imperfect information is known to be hard. In this paper, we propose translations of ATLir formulae that provide lower and upper bounds for their truth values, and are cheaper to verify than the original specifications. Most interestingly, the lower approximation is provided by a fixpoint expression that uses a nonstandard variant of the next-step ability operator. We show the correctness of the translations, establish their computational complexity, and validate the approach by experiments with a scalable scenario of Bridge play.

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Learning in the Machine: Random Backpropagation and the Learning Channel. (arXiv:1612.02734v1 [cs.LG])

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement of maintaining symmetric weights in a physical neural system. To better understand random backpropagation, we first connect it to the notions of local learning and the learning channel. Through this connection, we derive several alternatives to RBP, including skipped RBP (SRPB), adaptive RBP (ARBP), sparse RBP, and their combinations (e.g. ASRBP) and analyze their computational complexity. We then study their behavior through simulations using the MNIST and CIFAR-10 bechnmark datasets. These simulations show that most of these variants work robustly, almost as well as backpropagation, and that multiplication by the derivatives of the activation functions is important. As a follow-up, we study also the low-end of the number of bits required to communicate error information over the learning channel. We then provide partial intuitive explanations for some of the remarkable properties of RBP and its variations. Finally, we prove several mathematical results, including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.

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Controlling Robot Morphology from Incomplete Measurements. (arXiv:1612.02739v1 [cs.RO])

Mobile robots with complex morphology are essential for traversing rough terrains in Urban Search & Rescue missions (USAR). Since teleoperation of the complex morphology causes high cognitive load of the operator, the morphology is controlled autonomously. The autonomous control measures the robot state and surrounding terrain which is usually only partially observable, and thus the data are often incomplete. We marginalize the control over the missing measurements and evaluate an explicit safety condition. If the safety condition is violated, tactile terrain exploration by the body-mounted robotic arm gathers the missing data.

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Coupling Distributed and Symbolic Execution for Natural Language Queries. (arXiv:1612.02741v1 [cs.LG])

Building neural networks to query a knowledge base (a table) with natural language is an emerging research topic in NLP. The neural enquirer typically necessitates multiple steps of execution because of the compositionality of queries. In previous studies, researchers have developed either distributed enquirers or symbolic ones for table querying. The distributed enquirer is end-to-end learnable, but is weak in terms of execution efficiency and explicit interpretability. The symbolic enqurier, on the contrary, is efficient during execution; but it is very difficult to train especially at initial stages. In this paper, we propose to couple distributed and symbolic execution for natural language queries. The observation is that a fully distributed executor also exhibits meaningful, albeit imperfect, interpretation. We can thus pretrain the symbolic executor with the distributed one's intermediate execution results in a step-by-step fashion. Experiments show that our approach significantly outperforms either the distributed or symbolic executor; moreover, we have recovered more than 80% execution sequences with only groundtruth denotations during training. In summary, the coupled neural enquirer takes advantages of both distributed and symbolic executors, and has high performance, high learning efficiency, high execution efficiency, and high interpretability.

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Hierarchy through Composition with Linearly Solvable Markov Decision Processes. (arXiv:1612.02757v1 [cs.AI])

Hierarchical architectures are critical to the scalability of reinforcement learning methods. Current hierarchical frameworks execute actions serially, with macro-actions comprising sequences of primitive actions. We propose a novel alternative to these control hierarchies based on concurrent execution of many actions in parallel. Our scheme uses the concurrent compositionality provided by the linearly solvable Markov decision process (LMDP) framework, which naturally enables a learning agent to draw on several macro-actions simultaneously to solve new tasks. We introduce the Multitask LMDP module, which maintains a parallel distributed representation of tasks and may be stacked to form deep hierarchies abstracted in space and time.

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Safety Verification and Control for Collision Avoidance at Road Intersections. (arXiv:1612.02795v1 [math.OC])

This paper presents the design of a supervisory algorithm that monitors safety at road intersections and overrides drivers with a safe input when necessary. The design of the supervisor consists of two parts: safety verification and control design. Safety verification is the problem to determine if vehicles will be able to cross the intersection without colliding with current drivers' inputs. We translate this safety verification problem into a jobshop scheduling problem, which minimizes the maximum lateness and evaluates if the optimal cost is zero. The zero optimal cost corresponds to the case in which all vehicles can cross each conflict area without collisions. Computing the optimal cost requires solving a Mixed Integer Nonlinear Programming (MINLP) problem due to the nonlinear second-order dynamics of the vehicles. We therefore estimate this optimal cost by formulating two related Mixed Integer Linear Programming (MILP) problems that assume simpler vehicle dynamics. We prove that these two MILP problems yield lower and upper bounds of the optimal cost. We also quantify the worst case approximation errors of these MILP problems. We design the supervisor to override the vehicles with a safe control input if the MILP problem that computes the upper bound yields a positive optimal cost. We theoretically demonstrate that the supervisor keeps the intersection safe and is non-blocking. Computer simulations further validate that the algorithms can run in real time for problems of realistic size.

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Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification. (arXiv:1612.02814v1 [cs.LG])

In this paper, we study the problem of author identification under double-blind review setting, which is to identify potential authors given information of an anonymized paper. Different from existing approaches that rely heavily on feature engineering, we propose to use network embedding approach to address the problem, which can automatically represent nodes into lower dimensional feature vectors. However, there are two major limitations in recent studies on network embedding: (1) they are usually general-purpose embedding methods, which are independent of the specific tasks; and (2) most of these approaches can only deal with homogeneous networks, where the heterogeneity of the network is ignored. Hence, challenges faced here are two folds: (1) how to embed the network under the guidance of the author identification task, and (2) how to select the best type of information due to the heterogeneity of the network.

To address the challenges, we propose a task-guided and path-augmented heterogeneous network embedding model. In our model, nodes are first embedded as vectors in latent feature space. Embeddings are then shared and jointly trained according to task-specific and network-general objectives. We extend the existing unsupervised network embedding to incorporate meta paths in heterogeneous networks, and select paths according to the specific task. The guidance from author identification task for network embedding is provided both explicitly in joint training and implicitly during meta path selection. Our experiments demonstrate that by using path-augmented network embedding with task guidance, our model can obtain significantly better accuracy at identifying the true authors comparing to existing methods.

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Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization. (arXiv:1412.4972v4 [cs.AI] UPDATED)

The max-product Belief Propagation (BP) is a popular message-passing heuristic for approximating a maximum-a-posteriori (MAP) assignment in a joint distribution represented by a graphical model (GM). In the past years, it has been shown that BP can solve a few classes of Linear Programming (LP) formulations to combinatorial optimization problems including maximum weight matching, shortest path and network flow, i.e., BP can be used as a message-passing solver for certain combinatorial optimizations. However, those LPs and corresponding BP analysis are very sensitive to underlying problem setups, and it has been not clear what extent these results can be generalized to. In this paper, we obtain a generic criteria that BP converges to the optimal solution of given LP, and show that it is satisfied in LP formulations associated to many classical combinatorial optimization problems including maximum weight perfect matching, shortest path, traveling salesman, cycle packing, vertex/edge cover and network flow.

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An unexpected unity among methods for interpreting model predictions. (arXiv:1611.07478v3 [cs.AI] UPDATED)

Understanding why a model made a certain prediction is crucial in many data science fields. Interpretable predictions engender appropriate trust and provide insight into how the model may be improved. However, with large modern datasets the best accuracy is often achieved by complex models even experts struggle to interpret, which creates a tension between accuracy and interpretability. Recently, several methods have been proposed for interpreting predictions from complex models by estimating the importance of input features. Here, we present how a model-agnostic additive representation of the importance of input features unifies current methods. This representation is optimal, in the sense that it is the only set of additive values that satisfies important properties. We show how we can leverage these properties to create novel visual explanations of model predictions. The thread of unity that this representation weaves through the literature indicates that there are common principles to be learned about the interpretation of model predictions that apply in many scenarios.

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[FD] AST-2016-009:

Asterisk Project Security Advisory - ASTERISK-2016-009 Product Asterisk Summary Nature of Advisory Authentication Bypass Susceptibility Remote unauthenticated sessions Severity Minor Exploits Known No Reported On October 3, 2016 Reported By Walter Doekes Posted On Last Updated On December 8, 2016 Advisory Contact Mmichelson AT digium DOT com CVE Name Description The chan_sip channel driver has a liberal definition for whitespace when attempting to strip the content between a SIP header name and a colon character. Rather than following RFC 3261 and stripping only spaces and horizontal tabs, Asterisk treats any non-printable ASCII character as if it were whitespace. This means that headers such as Contact\x01: will be seen as a valid Contact header. This mostly does not pose a problem until Asterisk is placed in tandem with an authenticating SIP proxy. In such a case, a crafty combination of valid and invalid To headers can cause a proxy to allow an INVITE request into Asterisk without authentication since it believes the request is an in-dialog request. However, because of the bug described above, the request will look like an out-of-dialog request to Asterisk. Asterisk will then process the request as a new call. The result is that Asterisk can process calls from unvetted sources without any authentication. If you do not use a proxy for authentication, then this issue does not affect you. If your proxy is dialog-aware (meaning that the proxy keeps track of what dialogs are currently valid), then this issue does not affect you. If you use chan_pjsip instead of chan_sip, then this issue does not affect you. Resolution chan_sip has been patched to only treat spaces and horizontal tabs as whitespace following a header name. This allows for Asterisk and authenticating proxies to view requests the same way Affected Versions Product Release Series Asterisk Open Source 11.x All Releases Asterisk Open Source 13.x All Releases Asterisk Open Source 14.x All Releases Certified Asterisk 13.8 All Releases Corrected In Product Release Asterisk Open Source 11.25.1, 13.13.1, 14.2.1 Certified Asterisk 11.6-cert16, 13.8-cert4 Patches SVN URL Revision Links Asterisk Project Security Advisories are posted at http://ift.tt/12wGWyz This document may be superseded by later versions; if so, the latest version will be posted at http://ift.tt/2ggepnS and http://ift.tt/2ghjocO Revision History Date Editor Revisions Made November 28, 2016 Mark Michelson Initial writeup Asterisk Project Security Advisory - ASTERISK-2016-009 Copyright (c) 2016 Digium, Inc. All Rights Reserved. Permission is hereby granted to distribute and publish this advisory in its original, unaltered form.

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[FD] AST-2016-008: Crash on SDP offer or answer from endpoint using Opus

Asterisk Project Security Advisory - AST-2016-008 Product Asterisk Summary Crash on SDP offer or answer from endpoint using Opus Nature of Advisory Remote Crash Susceptibility Remote unauthenticated sessions Severity Critical Exploits Known No Reported On November 11, 2016 Reported By jorgen Posted On Last Updated On November 15, 2016 Advisory Contact jcolp AT digium DOT com CVE Name Description If an SDP offer or answer is received with the Opus codec and with the format parameters separated using a space the code responsible for parsing will recursively call itself until it crashes. This occurs as the code does not properly handle spaces separating the parameters. This does NOT require the endpoint to have Opus configured in Asterisk. This also does not require the endpoint to be authenticated. If guest is enabled for chan_sip or anonymous in chan_pjsip an SDP offer or answer is still processed and the crash occurs. Resolution The code has been updated to properly handle spaces separating parameters in the fmtp line. Upgrade to a released version with the fix incorporated or apply patch. Affected Versions Product Release Series Asterisk Open Source 13.x 13.12.0 and higher Asterisk Open Source 14.x All Versions Corrected In Product Release Asterisk Open Source 13.13.1, 14.2.1 Patches SVN URL Revision http://ift.tt/2ghl06A Asterisk 13 http://ift.tt/2gg6sze Asterisk 14 Links http://ift.tt/2ghjm4G Asterisk Project Security Advisories are posted at http://ift.tt/12wGWyz This document may be superseded by later versions; if so, the latest version will be posted at http://ift.tt/2ghmFcj and http://ift.tt/2ggcjUX Revision History Date Editor Revisions Made November 15, 2016 Joshua Colp Initial draft of Advisory Asterisk Project Security Advisory - AST-2016-008 Copyright 2016 Digium, Inc. All Rights Reserved. Permission is hereby granted to distribute and publish this advisory in its original, unaltered form.

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Rumor Central: Orioles have discussed trade for OF Jarrod Dyson with Royals - FanRag Sports; 30 SBs in 2016 (ESPN)

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Yahoo Flaw Allowed Hackers to Read Anyone's Emails

Yahoo has patched a critical security vulnerability in its Mail service that could have allowed an attacker to spy on any Yahoo user's inbox. Jouko Pynnönen, a Finnish Security researcher from security firm Klikki Oy, reported a DOM based persistent XSS (Cross-Site Scripting) in Yahoo mail, which if exploited, allows an attacker to send emails embedded with malicious code. <!-- adsense --> In

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Russia proposes 10 Year in Prison Sentence for Hackers and Malware Authors

The Russian government has introduced a draft bill that proposes prison sentences as punishment for hackers and cyber criminals creating malicious software used in targeting critical Russian infrastructure, even if they have no part in actual cyber attacks. The bill, published on the Russian government’s website on Wednesday, proposes amendments to the Russian Criminal Code and Criminal

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ISS Daily Summary Report – 12/07/2016

Story Time From Space Demo: The crew recorded a narrated video that pairs with the books Max Goes to Mars and Max Goes to Jupiter, that  demonstrates how in the absence of compressive forces exerted by the earth’s gravity, the human body grows/stretches. Story Time From Space combines science literacy outreach with simple demonstrations recorded aboard the International Space Station (ISS). Crew members read five science, technology, engineering and mathematics-related children’s books in orbit, and complete simple science concept experiments. Crew members videotape themselves reading the books and completing demonstrations. Video and data collected during the demonstrations are downlinked to the ground and posted in a video library with accompanying educational materials.  Fluid Shifts: The crew performed the final day for the Fluid Shift operations in the Russian Service Module (SM) for their Flight Day 45 session.  The subject donned the Lower Body Negative Pressure (LBNP/Chibis) device, while the operator, with ground support in Moscow, assisted in the medical monitoring.  Additionally, while the subject was in the LBNP and experiencing the negative pressure (pulling the fluid feetward), the Crew Medical Officer performed Distortion Product Otoacoustic Emissions (DPOAE), Optical Coherence Tomography (OCT), and Tonometry measurements. Fluid Shifts is a joint NASA-Russian experiment that investigates the causes for severe and lasting physical changes to astronaut’s eyes. Because the headward fluid shift is a hypothesized contributor to these changes, reversing this fluid shift with a lower body negative pressure device is investigated as a possible intervention. Results from this study may help to develop preventative measures against lasting changes in vision and eye damage.  Japanese Experiment Module (JEM) Airlock Slide Table Reconfiguration: With the completion of the Robotics External Leak Locator (RELL) checkout, the crew extended the JEM Slide Table into the module and removed the RELL and JEM On-orbit Replacement Units (ORU) Transfer Interface (JOTI).  The crew then installed the Small Fine Arm Attachment Mechanism (SAM) and Multi-Purpose Experiment Platform (MPEP) in preparation for the Japanese Small Satellite Orbital Deployers (J-SSOD) to be delivered on HTV-6.  The JOTI will be returned to its Pressurized Mating Adapter (PMA)-2 stowage location at a future time. Personal CO2 Monitor Calibration: Prior to next week’s long duration Personal CO2 Monitor demonstration, the crew performed a calibration of the sensor, comparing the sensor’s readings to that of the Major Constituent Analyzer (MCA).  The Personal CO2 Monitor demonstrates a system capable of unobtrusively collecting and downlinking individual crew members’ CO2 exposure for weeks to months. This investigation evaluates wearability principles in microgravity and also demonstrates Modular Wearable Architecture Base Board, allowing rapid certification of future wearable devices.  EVERYWEAR Tonometry: The crew performed the first session of the Everywear Tonometry test.  By connecting the Tonometer and the EveryWear application on the iPad, the crew was able to monitor and record pulse waves of the carotid and radial arteries. The EVERYWEAR assistant is an ambulatory data collection system that makes use of wearable sensors connected to a space station iPad tablet computer, which itself, is wirelessly synchronized with computers on the ground. This easy-use system seeks to demonstrate the benefits of extensive physiology data collection for both science and medical follow-up purposes, by improving usability for crew members on the ISS. The main advantage of EVERYWEAR is the ability to aggregate data from different tools, but it also brings with it a simplification in procedures for astronauts. This is a versatile device that can cover a wide variety of needs with a tailored data collection capability that allows a unified treatment of data. The use of this personal assistant brings a very important gain in crew-time availability for ISS crew members.  Meteor Grating Exchange: Today the diffraction grating on the Meteor camera located in the Window Observational Research Facility (WORF) was changed from a fine to a coarse grating. By changing the grating, the scientists are able to observe different frequencies of light. The Meteor payload is a visible spectroscopy instrument with the primary purpose of observing meteors in Earth orbit. Meteor uses image analysis to provide information on the physical and chemical properties of the meteoroid dust, such as size, density, and chemical composition. Since the parent comets or asteroids for most of the meteor showers are identified, the study of the meteoroid dust on orbit provides information about the parent comets and asteroids.  Optical PAyload for Lasercomm Science (OPALS):  OPALS flight software was updated on Tuesday to correct an issue with the laser RS-422 commanding interface. Yesterday the laser unit was powered on and the RS-422 commanding interface was initialized and verified by test. Following OPALS activation today and prior to the optical laser transmission over the Nice, France ground site, OPALS put itself into a “Safe State”.  OPALS is unable to assess and recover prior to the ground pass today, so these operations will be deferred until OPALS performs some troubleshooting steps today, looks at data, and reschedules this ground site opportunity. OPALS tests the potential for using a laser to transmit data to Earth from space.  Instead of being broadcast on radio waves, data is packaged onto beams of laser light and hardware on the International Space Station will point the laser to a receiver station on the ground. Radio waves transmission is limited by the speed that it can transfer data, but beaming information packages with lasers can greatly increase the amount of information transmitted over the same period of time.  Urine Processor Assembly (UPA) Troubleshooting:  The crew reconnected Fluids Control and Pump Assembly (FCPA) Quick Disconnect (QD)27 earlier today, this QD has been disconnected since GMT 322.  The UPA has been producing distillate with an elevated conductivity.  Sample results have determined Pre-Treated Urine (PTU) is in the purge distillate.  The source of PTU is either the FCPA or the Distillation Assembly (DA).  Troubleshooting involved disconnecting QD27 for two Advanced Recycle Filter Tank Assembly (ARFTA) concentration cycles to isolate the FCPA housing from the purge distillate.  Internal Thermal Control System (ITCS) Fluid System Servicer (FSS) Lab Refill Procedure Review: Today, the crew reviewed procedures […]

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Turkish Hackers Are Giving Away Prizes For Participating In DDoS Attacks

DDoS has become a game now that could knock any service offline. A Turkish hacking group is encouraging individuals to join its DDoS-for-Points platform that features points and prizes for carrying out distributed denial-of-service (DDoS) attacks against a list of predetermined targets. The points earned can later be redeemed for various online click-fraud and hacking tools. Dubbed Sath-ı

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What's happening at the center of elliptical galaxy NGC 4696? There, long tendrils of gas and dust have been imaged in great detail as shown by this recently released image from the Hubble Space Telescope. These filaments appear to connect to the central region of the galaxy, a region thought occupied by a supermassive black hole. Speculation holds that this black hole pumps out energy that heats surrounding gas, pushes out cooler filaments of gas and dust, and shuts down star formation. Balanced by magnetic fields, these filaments then appear to spiral back in toward and eventually circle the central black hole. NGC 4696 is the largest galaxy in the Centaurus Cluster of Galaxies, located about 150 million light years from Earth. The featured image shows a region about 45,000 light years across. via NASA http://ift.tt/2gaBLeE

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Effect of Reward Function Choices in Risk-Averse Reinforcement Learning. (arXiv:1612.02088v1 [cs.AI])

This paper studies Value-at-Risk problems in finite-horizon Markov decision processes (MDPs) with finite state space and two forms of reward function. Firstly we study the effect of reward function on two criteria in a short-horizon MDP. Secondly, for long-horizon MDPs, we estimate the total reward distribution in a finite-horizon Markov chain (MC) with the help of spectral theory and the central limit theorem, and present a transformation algorithm for the MCs with a three-argument reward function and a salvage reward.

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A Multi-Pass Approach to Large-Scale Connectomics. (arXiv:1612.02120v1 [q-bio.QM])

The field of connectomics faces unprecedented "big data" challenges. To reconstruct neuronal connectivity, automated pixel-level segmentation is required for petabytes of streaming electron microscopy data. Existing algorithms provide relatively good accuracy but are unacceptably slow, and would require years to extract connectivity graphs from even a single cubic millimeter of neural tissue. Here we present a viable real-time solution, a multi-pass pipeline optimized for shared-memory multicore systems, capable of processing data at near the terabyte-per-hour pace of multi-beam electron microscopes. The pipeline makes an initial fast-pass over the data, and then makes a second slow-pass to iteratively correct errors in the output of the fast-pass. We demonstrate the accuracy of a sparse slow-pass reconstruction algorithm and suggest new methods for detecting morphological errors. Our fast-pass approach provided many algorithmic challenges, including the design and implementation of novel shallow convolutional neural nets and the parallelization of watershed and object-merging techniques. We use it to reconstruct, from image stack to skeletons, the full dataset of Kasthuri et al. (463 GB capturing 120,000 cubic microns) in a matter of hours on a single multicore machine rather than the weeks it has taken in the past on much larger distributed systems.

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Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming. (arXiv:1612.02161v1 [cs.AI])

A key limitation of sampling algorithms for approximate inference is that it is difficult to quantify their approximation error. Widely used sampling schemes, such as sequential importance sampling with resampling and Metropolis-Hastings, produce output samples drawn from a distribution that may be far from the target posterior distribution. This paper shows how to upper-bound the symmetric KL divergence between the output distribution of a broad class of sequential Monte Carlo (SMC) samplers and their target posterior distributions, subject to assumptions about the accuracy of a separate gold-standard sampler. The proposed method applies to samplers that combine multiple particles, multinomial resampling, and rejuvenation kernels. The experiments show the technique being used to estimate bounds on the divergence of SMC samplers for posterior inference in a Bayesian linear regression model and a Dirichlet process mixture model.

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Knowledge Representation in Graphs using Convolutional Neural Networks. (arXiv:1612.02255v1 [cs.AI])

Knowledge Graphs (KG) constitute a flexible representation of complex relationships between entities particularly useful for biomedical data. These KG, however, are very sparse with many missing edges (facts) and the visualisation of the mesh of interactions nontrivial. Here we apply a compositional model to embed nodes and relationships into a vectorised semantic space to perform graph completion. A visualisation tool based on Convolutional Neural Networks and Self-Organised Maps (SOM) is proposed to extract high-level insights from the KG. We apply this technique to a subset of CTD, containing interactions of compounds with human genes / proteins and show that the performance is comparable to the one obtained by structural models.

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Extend natural neighbor: a novel classification method with self-adaptive neighborhood parameters in different stages. (arXiv:1612.02310v1 [cs.AI])

Various kinds of k-nearest neighbor (KNN) based classification methods are the bases of many well-established and high-performance pattern-recognition techniques, but both of them are vulnerable to their parameter choice. Essentially, the challenge is to detect the neighborhood of various data sets, while utterly ignorant of the data characteristic. This article introduces a new supervised classification method: the extend natural neighbor (ENaN) method, and shows that it provides a better classification result without choosing the neighborhood parameter artificially. Unlike the original KNN based method which needs a prior k, the ENaNE method predicts different k in different stages. Therefore, the ENaNE method is able to learn more from flexible neighbor information both in training stage and testing stage, and provide a better classification result.

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Fair task allocation in transportation. (arXiv:1505.07434v3 [cs.AI] UPDATED)

Task allocation problems have traditionally focused on cost optimization. However, more and more attention is being given to cases in which cost should not always be the sole or major consideration. In this paper we study a fair task allocation problem in transportation where an optimal allocation not only has low cost but more importantly, it distributes tasks as even as possible among heterogeneous participants who have different capacities and costs to execute tasks. To tackle this fair minimum cost allocation problem we analyze and solve it in two parts using two novel polynomial-time algorithms. We show that despite the new fairness criterion, the proposed algorithms can solve the fair minimum cost allocation problem optimally in polynomial time. In addition, we conduct an extensive set of experiments to investigate the trade-off between cost minimization and fairness. Our experimental results demonstrate the benefit of factoring fairness into task allocation. Among the majority of test instances, fairness comes with a very small price in terms of cost.

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Chinese Poetry Generation with Planning based Neural Network. (arXiv:1610.09889v2 [cs.CL] UPDATED)

Chinese poetry generation is a very challenging task in natural language processing. In this paper, we propose a novel two-stage poetry generating method which first plans the sub-topics of the poem according to the user's writing intent, and then generates each line of the poem sequentially, using a modified recurrent neural network encoder-decoder framework. The proposed planning-based method can ensure that the generated poem is coherent and semantically consistent with the user's intent. A comprehensive evaluation with human judgments demonstrates that our proposed approach outperforms the state-of-the-art poetry generating methods and the poem quality is somehow comparable to human poets.

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Tuning Recurrent Neural Networks with Reinforcement Learning. (arXiv:1611.02796v3 [cs.LG] UPDATED)

Sequence models can be trained using supervised learning and a next-step prediction objective. This approach, however, suffers from known failure modes. For example, it is notoriously difficult to ensure multi-step generated sequences have coherent global structure. Motivated by the fact that reinforcement learning (RL) can be used to impose arbitrary properties on generated data by choosing appropriate reward functions, in this paper we propose a novel approach for sequence training which combines Maximum Likelihood (ML) and RL training. We refine a sequence predictor by optimizing for some imposed reward functions, while maintaining good predictive properties learned from data. We propose efficient ways to solve this by augmenting deep Q-learning with a cross-entropy reward and deriving novel off-policy methods for RNNs from stochastic optimal control (SOC). We explore the usefulness of our approach in the context of music generation. An LSTM is trained on a large corpus of songs to predict the next note in a musical sequence. This Note-RNN is then refined using RL, where the reward function is a combination of rewards based on rules of music theory, as well as the output of another trained Note-RNN. We show that by combining ML and RL, this RL Tuner method can not only produce more pleasing melodies, but that it can significantly reduce unwanted behaviors and failure modes of the RNN.

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Composing Music with Grammar Argumented Neural Networks and Note-Level Encoding. (arXiv:1611.05416v2 [cs.LG] UPDATED)

Creating aesthetically pleasing pieces of art, including music, has been a long-term goal for artificial intelligence research. Despite recent successes of long-short term memory (LSTM) recurrent neural networks (RNNs) in sequential learning, LSTM neural networks have not, by themselves, been able to generate natural-sounding music conforming to music theory. To transcend this inadequacy, we put forward a novel method for music composition that combines the LSTM with Grammars motivated by music theory. The main tenets of music theory are encoded as grammar argumented (GA) filters on the training data, such that the machine can be trained to generate music inheriting the naturalness of human-composed pieces from the original dataset while adhering to the rules of music theory. Unlike previous approaches, pitches and durations are encoded as one semantic entity, which we refer to as note-level encoding. This allows easy implementation of music theory grammars, as well as closer emulation of the thinking pattern of a musician. Although the GA rules are applied to the training data and never directly to the LSTM music generation, our machine still composes music that possess high incidences of diatonic scale notes, small pitch intervals and chords, in deference to music theory.

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The BIN_COUNTS Constraint: Filtering and Applications. (arXiv:1611.08942v2 [cs.AI] UPDATED)

We introduce the BIN_COUNTS constraint, which deals with the problem of counting the number of decision variables in a set which are assigned values that lie in given bins. We illustrate a decomposition and a filtering algorithm that achieves generalised arc consistency. We contrast the filtering power of these two approaches and we discuss a number of applications. We show that BIN_COUNTS can be employed to develop a decomposition for the $\chi^2$ test constraint, a new statistical constraint that we introduce in this work. We also show how this new constraint can be employed in the context of the Balanced Academic Curriculum Problem and of the Balanced Nursing Workload Problem. For both these problems we carry out numerical studies involving our reformulations. Finally, we present a further application of the $\chi^2$ test constraint in the context of confidence interval analysis.

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One Anonymous Syrian Collective's Struggle Against the Spectacle of Indignity

One anonymous collective of Syrian filmmakers and activists is fighting against this phenomenon. Members of this group, called AbouNaddara, ...

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Grant anonymous access to a folder

I want to grant anonymous, perpetual access to a folder in my Sharefile. I will post documents here on an ongoing basis and I want dozens of unknown ...

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NFL Image: Ravens' Steve Smith Sr. wears Yoda costume while addressing media; "been a few decades since I wore a onesie" (ESPN)

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Feinstein: A Message To Anonymous Dope Bowl Official

I've said this before, I'll say it again: Anonymous quotes are a pox on my profession. They're a copout, both for the guy hiding behind anonymity and ...

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Anonymous

Find & apply online for the latest Jobs from Anonymous with reed.co.uk, the UK's #1 job site.

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I have a new follower on Twitter

Perseids Project
Perseids enables engagement of students and scholars at all levels of expertise to create, share and publish their data and research practices.
Medford, MA
https://t.co/vD7K9zJi16
Following: 5002 - Followers: 3662

December 07, 2016 at 01:28PM via Twitter http://twitter.com/PerseidsProject

Orioles not interested in Jose Bautista, because "our fans don't like" him, GM Dan Duquette tells Sportsnet Radio 590 (ESPN)

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Hacker who stole Celebrity Emails, Sex Tapes, Movie Scripts Gets 5 Years in Prison

A hacker who was arrested last year for hacking into celebrities' email accounts to steal the unreleased movie and television scripts, their private messages, and sex tapes to sell them has finally been sentenced five years in prison. Alonzo Knowles, a 24-year-old Bahamian man, was convicted by U.S. District Judge Paul A. Engelmayer in Manhattan on Tuesday. Knowles, who maintained a list of

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Anonymous Hamburger Society

Anonymous Hamburger Society, on siteInspire: a showcase of the best web design inspiration.

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5-Year-Old Linux Kernel Local Privilege Escalation Flaw Discovered

A 5-year-old serious privilege-escalation vulnerability has been discovered in Linux kernel that affects almost every distro of the Linux operating system, including Redhat, and Ubuntu. Over a month back, a nine-year-old privilege-escalation vulnerability, dubbed "Dirty COW," was discovered in the Linux kernel that affected every distro of the open-source operating system, including Red Hat,

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advagg exchanges domain for server ip to link css for anonymous users [#2833643] | Drupal.org

For a logged in user the css is linked like this but for anonymous users the css is linked like this Why does it exchange the domain name for the ip?

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ISS Daily Summary Report – 12/06/2016

Space Station Remote Manipulator System (SSRMS) Operations:  Monday afternoon and overnight, Robotics Ground Controllers powered up the Mobile Serving System (MSS) and configured the SSRMS and Special Purpose Dexterous Manipulator (SPDM) Arm2 for translation.  They then translated the Mobile Transporter (MT) translation from Worksite(WS)7 to WS5, stowed the SPDM on the Lab, and walked the SSRMS onto Node 2.  As part of HTV-6 pre-launch checkouts, Diagnostics and Checkouts of the Payload Orbital Replacement Unit (ORU) Accommodation (POA) (on Prime String) and SSRMS LEE were performed along with the brakes Diagnostics (on both Strings).  Afterward, a checkout of the SSRMS Latch End Effector (LEE) Dual Stage Carriage Rates (DSCR) and the POA diagnostics and checkouts on the redundant power string were performed. H-II Transfer Vehicle (HTV) Onboard Training (OBT):  Today, the Robotics Ground Controllers powered up the MSS in preparation for the HTV-6 Offset Grapples Practice Session.  During the training session, the crew practiced maneuvering the SSRMS into the grapple envelope of the Permanent Multipurpose Module (PMM) PDGF.  They performed this maneuver several times and then performed a run during which the Robotics Ground Controllers safed the SSRMS to simulate a failure. After the Offset Grapples practice session, the SSRMS was maneuvered to the HTV-6 High Hover position ready for HTV-6 capture scheduled for 13-December. Fluid Shifts: Today was the first of two days of Flight Day 45 (FD45) Fluid Shifts operations performed in the Russian Segment, utilizing the Lower Body Negative Pressure (LBNP/Chibis).  The subject donned the Chibis device, and while the crewmember was exposed to the negative pressure (pulling the fluid feetward), the operator, with remote guidance from Houston, performed arterial and venous measurements of the head and neck; cardiac, ophthalmic, and portal vein measurements; and tissue thickness of various body parts using the Human Research Facility (HRF) ultrasound.  The crew then deconfigured the ultrasound, and configured the Cerebral and Cochlear Fluid Pressure (CCFP) and Distortion Product Otoacoustic Emissions (DPOAE) for tomorrow’s operations. Fluid Shifts investigates the causes for severe and lasting physical changes to astronaut’s eyes. Because the headward fluid shift is a hypothesized contributor to these changes, reversing this fluid shift with a lower body negative pressure device is investigated as a possible intervention. Results from this study may help to develop preventative measures against lasting changes in vision and eye damage. Fine Motor Skills: The crew performed their FD20 Fine Motor Skills tests, performing a series of interactive tasks on a touchscreen tablet. The investigation studies how fine motor skills are effected by long-term microgravity exposure, different phases of microgravity adaptation, and sensorimotor recovery after returning to Earth gravity. The goal of Fine Motor Skills is to answer how fine motor performance in microgravity trend/vary over the duration of a six-month and year-long space mission; how fine motor performance on orbit compare with that of a closely matched participant on Earth; and how performance trend/vary before and after gravitational transitions, including the periods of early flight adaptation, and very early/near immediate post-flight periods. Electrostatic Levitation Furnace (ELF) Sample Holder Exchange: On December 2, the crew removed the samples from the ELF Work Volume and cleaned the internal chamber.  Today, the sample cartridge was removed and replaced with a new sample and then reconnected and integrated in the ELF. The Electrostatic Levitation Furnace (ELF) is an experimental facility designed to levitate/melt/solidify materials by containerless processing techniques using the Electrostatic Levitation method. With this facility, thermophysical properties of high temperature melts can be measured, and solidification from deeply undercooled melts can be achieved. The ELF is located in the JEM Multipurpose Small Payload Rack (MSPR) in Kibo.  Optical Payload for Lasercomm Science (OPALS):  Today, ground controllers will uplink a patch to the OPALS software, in an attempt to recover capability.  In July 2016, the laser modulation card that supplies data input to the OPALS laser failed.  The option of continuous wave laser operations (continuous ON rather than ON/OFF modulation) was investigated by the OPALS team and forward plan was approved by the Payload Safety Review Panel (PSRP).  During an attempted pass in September 2016, the laser unit was powered on with telemetry indicating nominal performance.  However, the OPALS flight software entered safe mode (with reboot) once the first laser command was sent.  Further investigation determined that the RS-422 commanding interface to the laser unit is not initialized in Version 1.4 in the event the laser modulation card is not detected.  The Version 1.5 update fixes this bug by initializing the RS-422 commanding interface when the laser modulation card is not detected. OPALS tests the potential for using a laser to transmit data to Earth from space.  Instead of being broadcast on radio waves, data is packaged onto beams of laser light and hardware on the ISS will point the laser to a receiver station on the ground. Radio waves transmission is limited by the speed that it can transfer data, but beaming information packages with lasers can greatly increase the amount of information transmitted over the same period of time. Japanese Experiment Module (JEM) Airlock (AL) Repress:  Following a week of Robotics External Leak Locator (RELL) operations, last weekend the Robotics Ground Team installed the RELL on the slide table followed by the slide table being retracted back into the JEM AL.  Earlier today the crew pressurized and performed a leak check of the JEM AL.  Tomorrow the crew is scheduled to remove the JEM ORU Xfer I/F (JOTI) and RELL from the slide table.  Oxygen Generator System (OGS) Flow Measurements:  Last night the Oxygen Generation Assembly (OGA) was commanded to Standby due to low air flow in the rack as measured by crew. This morning the crew repeated the flow measurements for the OGS Avionics Air Assembly (AAA). Today’s readings indicated 6.6 cubic feet per minute (cfm) which is nominal. No AAA cleaning is required at this time, and OGS has been reactivated.  Today’s Planned Activities All activities were completed unless otherwise noted.  Acoustic Dosimeter Setup Day 2 Fine Motor Skills Experiment Test – Subject FLUID SHIFTS. […]

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Hacking Millions with Just an Image — Recipe: Pixels, Ads & Exploit Kit

If you have visited any popular mainstream website over the past two months, your computer may have been infected — Thanks to a new exploit kit discovered by security researchers. Researchers from antivirus provider ESET released a report on Tuesday stating that they have discovered an exploit kit, dubbed Stegano, hiding malicious code in the pixels of banner advertisements that are currently

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Aurora over Jupiters South Pole from Juno

Why is there a glowing oval over Jupiter's South Pole? Aurora. Near the closest part of its first pass near Jupiter in August, NASA's robotic spacecraft Juno captured this dramatic infrared image of a bright auroral ring. Auroras are caused by high energy particles from the Sun interacting with a planet's magnetic field, and ovals around magnetic poles are common. Data from Juno are giving preliminary indications that Jupiter's magnetic field and aurorae are unexpectedly powerful and complex. Unfortunately, a computer glitch caused Juno to go into safe mode during its last pass near the Jovian giant in September. That glitch has now been resolved, making Juno ready for its next pass over Jupiter's cloud tops this coming Sunday. via NASA http://ift.tt/2h2oM3h

Rumor Central: Orioles have called about free-agent 1B Chris Carter - FanRag Sports; .222, NL-best 41 home runs in 2016 (ESPN)

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Stream Actors Anonymous Movie Online tube Full HD Quality|)@ Stream Actors Anonymous Movie Download Free. Streaming|(( Stream Actors ...

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Improving the Performance of Neural Networks in Regression Tasks Using Drawering. (arXiv:1612.01589v1 [cs.LG])

The method presented extends a given regression neural network to make its performance improve. The modification affects the learning procedure only, hence the extension may be easily omitted during evaluation without any change in prediction. It means that the modified model may be evaluated as quickly as the original one but tends to perform better.

This improvement is possible because the modification gives better expressive power, provides better behaved gradients and works as a regularization. The knowledge gained by the temporarily extended neural network is contained in the parameters shared with the original neural network.

The only cost is an increase in learning time.

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AI Researchers, Video Games Are Your Friends!. (arXiv:1612.01608v1 [cs.AI])

If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question "what can video games do for AI", and discusses how in particular general video game playing is the ideal testbed for artificial general intelligence research. It then asks the question "what can AI do for video games", and lays out a vision for what video games might look like if we had significantly more advanced AI at our disposal. The chapter is based on my keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad audience.

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Fleet Size and Mix Split-Delivery Vehicle Routing. (arXiv:1612.01691v1 [cs.AI])

In the classic Vehicle Routing Problem (VRP) a fleet of of vehicles has to visit a set of customers while minimising the operations' costs. We study a rich variant of the VRP featuring split deliveries, an heterogeneous fleet, and vehicle-commodity incompatibility constraints. Our goal is twofold: define the cheapest routing and the most adequate fleet.

To do so, we split the problem into two interdependent components: a fleet design component and a routing component. First, we define two Mixed Integer Programming (MIP) formulations for each component. Then we discuss several improvements in the form of valid cuts and symmetry breaking constraints.

The main contribution of this paper is a comparison of the four resulting models for this Rich VRP. We highlight their strengths and weaknesses with extensive experiments.

Finally, we explore a lightweight integration with Constraint Programming (CP). We use a fast CP model which gives good solutions and use the solution to warm-start our models.

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Factored Contextual Policy Search with Bayesian Optimization. (arXiv:1612.01746v1 [cs.LG])

Scarce data is a major challenge to scaling robot learning to truly complex tasks, as we need to generalize locally learned policies over different "contexts". Bayesian optimization approaches to contextual policy search (CPS) offer data-efficient policy learning that generalize over a context space. We propose to improve data- efficiency by factoring typically considered contexts into two components: target- type contexts that correspond to a desired outcome of the learned behavior, e.g. target position for throwing a ball; and environment type contexts that correspond to some state of the environment, e.g. initial ball position or wind speed. Our key observation is that experience can be directly generalized over target-type contexts. Based on that we introduce Factored Contextual Policy Search with Bayesian Optimization for both passive and active learning settings. Preliminary results show faster policy generalization on a simulated toy problem.

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On a Well-behaved Relational Generalisation of Rough Set Approximations. (arXiv:1612.01857v1 [cs.AI])

We examine non-dual relational extensions of rough set approximations and find an extension which satisfies surprisingly many of the usual rough set properties. We then use this definition to give an explanation for an observation made by Samanta and Chakraborty in their recent paper [P. Samanta and M.K. Chakraborty. Interface of rough set systems and modal logics: A survey. \textit{Transactions on Rough Sets XIX}, pages 114-137, 2015].

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Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning. (arXiv:1612.01887v1 [cs.CV])

Attention-based neural encoder-decoder frameworks have been widely adopted for image captioning. Most methods force visual attention to be active for every generated word. However, the decoder likely requires little to no visual information from the image to predict non-visual words such as "the" and "of". Other words that may seem visual can often be predicted reliably just from the language model e.g., "sign" after "behind a red stop" or "phone" following "talking on a cell". In this paper, we propose a novel adaptive attention model with a visual sentinel. At each time step, our model decides whether to attend to the image (and if so, to which regions) or to the visual sentinel. The model decides whether to attend to the image and where, in order to extract meaningful information for sequential word generation. We test our method on the COCO image captioning 2015 challenge dataset and Flickr30K. Our approach sets the new state-of-the-art by a significant margin.

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Cross-Lingual Predicate Mapping Between Linked Data Ontologies. (arXiv:1612.01892v1 [cs.AI])

Ontologies in different natural languages often differ in quality in terms of richness of schema or richness of internal links. This difference is markedly visible when comparing a rich English language ontology with a non-English language counterpart. Discovering alignment between them is a useful endeavor as it serves as a starting point in bridging the disparity. In particular, our work is motivated by the absence of inter-language links for predicates in the localised versions of DBpedia. In this paper, we propose and demonstrate an ad-hoc system to find possible owl:equivalentProperty links between predicates in ontologies of different natural languages. We seek to achieve this mapping by using pre-existing inter-language links of the resources connected by the given predicate. Thus, our methodology stresses on semantic similarity rather than lexical. Moreover, through an evaluation, we show that our system is capable of outperforming a baseline system that is similar to the one used in recent OAEI campaigns.

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Correlation Alignment for Unsupervised Domain Adaptation. (arXiv:1612.01939v1 [cs.CV])

In this chapter, we present CORrelation ALignment (CORAL), a simple yet effective method for unsupervised domain adaptation. CORAL minimizes domain shift by aligning the second-order statistics of source and target distributions, without requiring any target labels. In contrast to subspace manifold methods, it aligns the original feature distributions of the source and target domains, rather than the bases of lower-dimensional subspaces. It is also much simpler than other distribution matching methods. CORAL performs remarkably well in extensive evaluations on standard benchmark datasets. We first describe a solution that applies a linear transformation to source features to align them with target features before classifier training. For linear classifiers, we propose to equivalently apply CORAL to the classifier weights, leading to added efficiency when the number of classifiers is small but the number and dimensionality of target examples are very high. The resulting CORAL Linear Discriminant Analysis (CORAL-LDA) outperforms LDA by a large margin on standard domain adaptation benchmarks. Finally, we extend CORAL to learn a nonlinear transformation that aligns correlations of layer activations in deep neural networks (DNNs). The resulting Deep CORAL approach works seamlessly with DNNs and achieves state-of-the-art performance on standard benchmark datasets. Our code is available at:~\url{http://ift.tt/2g8wjJn}

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Coactive Critiquing: Elicitation of Preferences and Features. (arXiv:1612.01941v1 [cs.AI])

When faced with complex choices, users refine their own preference criteria as they explore the catalogue of options. In this paper we propose an approach to preference elicitation suited for this scenario. We extend Coactive Learning, which iteratively collects manipulative feedback, to optionally query example critiques. User critiques are integrated into the learning model by dynamically extending the feature space. Our formulation natively supports constructive learning tasks, where the option catalogue is generated on-the-fly. We present an upper bound on the average regret suffered by the learner. Our empirical analysis highlights the promise of our approach.

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Review of state-of-the-arts in artificial intelligence with application to AI safety problem. (arXiv:1605.04232v2 [cs.AI] UPDATED)

Here, I review current state-of-the-arts in many areas of AI to estimate when it's reasonable to expect human level AI development. Predictions of prominent AI researchers vary broadly from very pessimistic predictions of Andrew Ng to much more moderate predictions of Geoffrey Hinton and optimistic predictions of Shane Legg, DeepMind cofounder. Given huge rate of progress in recent years and this broad range of predictions of AI experts, AI safety questions are also discussed.

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Deviant Learning Algorithm: Learning Sparse Mismatch Representations through Time and Space. (arXiv:1609.01459v3 [cs.AI] UPDATED)

Predictive coding (PDC) has recently attracted attention in the neuroscience and computing community as a candidate unifying paradigm for neuronal studies and artificial neural network implementations particularly targeted at unsupervised learning systems. The Mismatch Negativity (MMN) has also recently been studied in relation to PC and found to be a useful ingredient in neural predictive coding systems. Backed by the behavior of living organisms, such networks are particularly useful in forming spatio-temporal transitions and invariant representations of the input world. However, most neural systems still do not account for large number of synapses even though this has been shown by a few machine learning researchers as an effective and very important component of any neural system if such a system is to behave properly. Our major point here is that PDC systems with the MMN effect in addition to a large number of synapses can greatly improve any neural learning system's performance and ability to make decisions in the machine world. In this paper, we propose a novel bio-mimetic computational intelligence algorithm -- the Deviant Learning Algorithm, inspired by these key ideas and functional properties of recent brain-cognitive discoveries and theories. We also show by numerical experiments guided by theoretical insights, how our invented bio-mimetic algorithm can achieve competitive predictions even with very small problem specific data.

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Contextual RNN-GANs for Abstract Reasoning Diagram Generation. (arXiv:1609.09444v2 [cs.CV] UPDATED)

Understanding, predicting, and generating object motions and transformations is a core problem in artificial intelligence. Modeling sequences of evolving images may provide better representations and models of motion and may ultimately be used for forecasting, simulation, or video generation. Diagrammatic Abstract Reasoning is an avenue in which diagrams evolve in complex patterns and one needs to infer the underlying pattern sequence and generate the next image in the sequence. For this, we develop a novel Contextual Generative Adversarial Network based on Recurrent Neural Networks (Context-RNN-GANs), where both the generator and the discriminator modules are based on contextual history (modeled as RNNs) and the adversarial discriminator guides the generator to produce realistic images for the particular time step in the image sequence. We evaluate the Context-RNN-GAN model (and its variants) on a novel dataset of Diagrammatic Abstract Reasoning, where it performs competitively with 10th-grade human performance but there is still scope for interesting improvements as compared to college-grade human performance. We also evaluate our model on a standard video next-frame prediction task, achieving improved performance over comparable state-of-the-art.

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