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Saturday, October 24, 2015
Ocean City, MD's surf is at least 5.42ft high
Ocean City, MD Summary
At 4:00 AM, surf min of 4.92ft. At 10:00 AM, surf min of 5.42ft. At 4:00 PM, surf min of 4.32ft. At 10:00 PM, surf min of 3.61ft.
Surf maximum: 5.68ft (1.73m)
Surf minimum: 5.42ft (1.65m)
Tide height: 4.36ft (1.33m)
Wind direction: SSE
Wind speed: 15.08 KTS
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Estoril scores late for 2-2 draw with Rio Ave in Portugal
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Sydney wins tight derby to go atop A-League table
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S. African Tokyo Sexwale says will run for FIFA president
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Aston Villa loses 2-1 at home to Swansea
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Goal-line technology helps Lorient to 1-1 draw with Rennes
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William & Mary's Business and Law Schools Share $44-Million Gift
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Ronaldo helps Madrid beat 10-man Celta 3-1
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Russia backs down on demand for Slutsky to leave CSKA
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Chelsea beaten 2-1 at West Ham, Aston Villa loses again
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Vardy scores again as Leicester beats Crystal Palace 1-0
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Ronaldo helps Madrid beat Celta 3-1
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Watford beats Stoke 2-0 in Premier League
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Bayern gets 1,000th Bundesliga victory, extends record start
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Empoli beats Genoa 2-0 ahead of Inter Milan match
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Hiroshima beats Kofu 2-0 to book spot in J-League postseason
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Hackers Find A Way To Disable Car Airbags System
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Hiroshima secures place in J-League championship
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Alcoholics Anonymous Humboldt Meetings
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Anonymous Bowl
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Starburst Galaxy Messier 94
Friday, October 23, 2015
US to move forward with hosting 2016 Copa America
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Ravens Video: Jamison Hensley says Steve Smith faces his biggest test of the season vs Cardinals CB Patrick Peterson (ESPN)
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Hamburg snatches 1-0 win at Hoffenheim in Bundesliga
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Rayo Vallecano beats Espanyol 3-0 in the Spanish league
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Nantes beats Caen 2-0 in French league
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UEFA fines England over crowd disturbances in Euro qualifier
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Narcotics Anonymous extends an invitation to professional workers
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Anonymous's Blog Posts
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Asylum-seeking Eritrea soccer players in detention center
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Moldova fined over racist flags in European qualifier
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Former German federation boss calls successor liar
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Hacking Fitbit Health Trackers Wirelessly in 10 Seconds
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ISS Daily Summary Report – 10/22/15
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TalkTalk Hacked; 4 Million Credit Card Profiles may have been Stolen
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Joomla 3.4.5 patches Critical SQL Injection Vulnerability
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Hacking CCTV Cameras to Launch DDoS Attacks
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Jerome Champagne enters FIFA presidential election contest
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FIFA urged to make human rights key to presidential race
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Star Factory Messier 17
Q&A with RaD-X Project Scientist, Erica Alston
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Thursday, October 22, 2015
NZ loses appeal against Olympic football ejection
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Police: Minnesota woman sent anonymous notes asking to...
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Generalized Shortest Path Kernel on Graphs. (arXiv:1510.06492v1 [cs.AI])
We consider the problem of classifying graphs using graph kernels. We define a new graph kernel, called the generalized shortest path kernel, based on the number and length of shortest paths between nodes. For our example classification problem, we consider the task of classifying random graphs from two well-known families, by the number of clusters they contain. We verify empirically that the generalized shortest path kernel outperforms the original shortest path kernel on a number of datasets. We give a theoretical analysis for explaining our experimental results. In particular, we estimate distributions of the expected feature vectors for the shortest path kernel and the generalized shortest path kernel, and we show some evidence explaining why our graph kernel outperforms the shortest path kernel for our graph classification problem.
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German football boss admits to FIFA payment ahead of WC
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Anonymous Calling App Launched at Amsterdam Privacy Week
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[FD] SEC Consult SA-20151022-0 :: Lime Survey Multiple Critical Vulnerabilities
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Column: PSG still not ready to scale Champions League peak
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Brazil brings back Neymar for World Cup qualifiers
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UEFA charges Man City for fans booing Champs League anthem
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Klopp challenges English FA over use of teenage player
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ISS Daily Summary Report – 10/21/15
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Bayern shooting for 1,000 Bundesliga win vs. Cologne
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Dutch football great Johan Cruyff has lung cancer
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German football boss again denies World Cup corruption
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Salah an issue as Roma visits Fiorentina in 1 vs. 2 matchup
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Real Madrid and Celta Vigo play for Spanish league lead
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City still Manchester's dominant force ahead of 161st derby
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Anonymous app helps police track down users who post threats
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PSG back to French league routine against Saint-Etienne
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Netherlands to play Wales, Germany in friendlies
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Italy to host fellow qualifier Romania in November friendly
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FIFA executive lineup of 2010 scores highly for bad behavior
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The Fractured North Pole of Saturns Enceladus
Carli Lloyd scores in 85th minute, US ties Brazil 1-1
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Wednesday, October 21, 2015
Alex Mogan plays for US while trade rumors swirl
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I have a new follower on Twitter
Wikilerts
A #Wiki for #Alerts. Create alert communities and get alerts for anything. #Crowdsourcing
http://t.co/6H1Ozl14D1
Following: 323 - Followers: 188
October 21, 2015 at 10:09PM via Twitter http://twitter.com/Wikilerts
Martial scores to rescue 1-1 draw for United at CSKA
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Injury-hit Real Madrid holds PSG 0-0 in Champions League
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High Performance Latent Variable Models. (arXiv:1510.06143v1 [cs.LG])
Latent variable models have accumulated a considerable amount of interest from the industry and academia for their versatility in a wide range of applications. A large amount of effort has been made to develop systems that is able to extend the systems to a large scale, in the hope to make use of them on industry scale data. In this paper, we describe a system that operates at a scale orders of magnitude higher than previous works, and an order of magnitude faster than state-of-the-art system at the same scale, at the same time showing more robustness and more accurate results.
Our system uses a number of advances in distributed inference: high performance in synchronization of sufficient statistics with relaxed consistency model; fast sampling, using the Metropolis-Hastings-Walker method to overcome dense generative models; statistical modeling, moving beyond Latent Dirichlet Allocation (LDA) to Pitman-Yor distributions (PDP) and Hierarchical Dirichlet Process (HDP) models; sophisticated parameter projection schemes, to resolve the conflicts within the constraint between parameters arising from the relaxed consistency model.
This work significantly extends the domain of applicability of what is commonly known as the Parameter Server. We obtain results with up to hundreds billion oftokens, thousands of topics, and a vocabulary of a few million token-types, using up to 60,000 processor cores operating on a production cluster of a large Internet company. This demonstrates the feasibility to scale to problems orders of magnitude larger than any previously published work.
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Creating Scalable and Interactive Web Applications Using High Performance Latent Variable Models. (arXiv:1510.06153v1 [cs.AI])
In this project we outline a modularized, scalable system for comparing Amazon products in an interactive and informative way using efficient latent variable models and dynamic visualization. We demonstrate how our system can build on the structure and rich review information of Amazon products in order to provide a fast, multifaceted, and intuitive comparison. By providing a condensed per-topic comparison visualization to the user, we are able to display aggregate information from the entire set of reviews while providing an interface that is at least as compact as the "most helpful reviews" currently displayed by Amazon, yet far more informative.
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Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems. (arXiv:1510.06335v1 [cs.AI])
Crowdsourcing systems commonly face the problem of aggregating multiple judgments provided by possibly unreliable workers. In addition, several aspects of the design of efficient crowdsourcing processes, such as defining worker's bonuses, fair prices and time limits of the tasks, involve the knowledge of the actual duration of a specific task. In this work, we introduce a new time{sensitive Bayesian aggregation method that simultaneously estimates a task's duration and obtains reliable aggregations of crowdsourced judgments. Our method builds on the key insight that the time taken by a worker to perform a task is an important indicator of the likely quality of the produced judgment. To capture this, our model uses latent variables to represent the uncertainty about the workers' completion time, the tasks' duration and the workers' accuracy. To relate the quality of a judgment to the time a worker spends on a task, our model assumes that each task is completed within a latent time window within which all workers with a propensity to valid labelling are expected to submit their judgments. In contrast, workers with a lower propensity to valid labelling, such as spammers, bots or lazy labellers, are assumed to perform tasks considerably faster or slower than the time required by normal workers. Specifically, we use efficient message- passing Bayesian inference to learn approximate posterior probabilities of (i) the confusion matrix of each worker, (ii) the propensity to valid labelling of each worker, (iii) the unbiased duration of each task and (iv) the true label of each task. Using two real-world public datasets for entity linking tasks, we show that our method produces up to 15% more accurate classifications and up to 100% more informative estimates of a task's duration compared to state{of{the{art methods.
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FIFA executive lineup of 2010 scores highly for bad behavior
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Madrid and PSG draw in Champions League; City wins late
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2016 Copa could move forward after marketing deals end
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Juventus keeps group lead after drawing 0-0 with 'Gladbach
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Malmo beats Shakhtar Donetsk 1-0 in Group A
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Galatasaray back in business in Europe with win over Benfica
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De Bruyne scores late winner, Man City beats Sevilla 2-1
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Atletico Madrid easily beats Astana 4-0 in Champions League
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Wolfsburg beats PSV Eindhoven 2-0 in Champions League
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[FD] Simple PHP static code analysis for security researchers
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[FD] SiteWIX - (edit_photo2.php id) SQL Injection Exploit
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[FD] APPLE-SA-2015-10-21-8 OS X Server 5.0.15
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[FD] APPLE-SA-2015-10-21-7 Xcode 7.1
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[FD] APPLE-SA-2015-10-21-5 iTunes 12.3.1
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[FD] APPLE-SA-2015-10-21-4 OS X El Capitan 10.11.1 and Security Update 2015-007
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[FD] APPLE-SA-2015-10-21-3 Safari 9.0.1
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US women to play China on Dec 13 at Glendale, Arizona
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WikiLeaks obtains CIA Director's Hacked Emails and Plans to Publish them Shortly
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Ravens: Former Baltimore LB Ray Lewis coming up live on SportsCenter on ESPN and WatchESPN (ESPN)
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German great Beckenbauer targeted in FIFA ethics probe
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Regional chiefs step up pressure on German federation boss
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The Latest: Beckenbauer, Villar under FIFA investigation
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Ocean City, MD's surf is at least 5.42ft high
Ocean City, MD Summary
At 4:00 AM, surf min of 4.82ft. At 10:00 AM, surf min of 5.42ft. At 4:00 PM, surf min of 3.2ft. At 10:00 PM, surf min of 3.69ft.
Surf maximum: 6.43ft (1.96m)
Surf minimum: 5.42ft (1.65m)
Tide height: 3.49ft (1.06m)
Wind direction: ENE
Wind speed: 15.4 KTS
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ISS Daily Summary Report – 10/20/15
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FIFA lets Palestinians host Saudis in World Cup qualifier
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Apple told Judge: It's Impossible to Access Data on Locked iPhones
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Mourinho says referee was 'weak' after Champs League draw
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Let's Encrypt Free SSL/TLS Certificate Now Trusted by Major Web Browsers
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How Hackers Can Hack Your Chip-and-PIN Credit Cards
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Dwight Lodeweges quits as coach of Dutch club Heerenveen
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The Latest: Chung accuses FIFA of sabotaging election bid
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Social Engineering — Free Online Training for Hackers
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[FD] [SE-2014-02] Google App Engine Java security sandbox bypasses (Issue 42)
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Cracking WiFi Passwords By Hacking into Smart Kettles
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2017 Eclipse: Earth, Moon and Sun
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Tuesday, October 20, 2015
US women ready for next stage of victory tour
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State government looks at law changes stop A-League flares
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Fact Checking in Large Knowledge Graphs - A Discriminative Predicate Path Mining Approach. (arXiv:1510.05911v1 [cs.DB])
Traditional fact checking by experts and analysts cannot keep pace with the volume of newly created information. It is important and necessary, therefore, to enhance our ability to computationally determine whether some statement of fact is true or false. We view this problem as a link-prediction task in a knowledge graph, and show that a new model of the top discriminative predicate paths is able to understand the meaning of some statement and accurately determine its veracity. We evaluate our approach by examining thousands of claims related to history, geography, biology, and politics using a public, million node knowledge graph extracted from Wikipedia and PubMedDB. Not only does our approach significantly outperform related models, we also find that the discriminative predicate path model is easily interpretable and provides sensible reasons for the final determination.
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Semantic, Cognitive, and Perceptual Computing: Advances toward Computing for Human Experience. (arXiv:1510.05963v1 [cs.AI])
The World Wide Web continues to evolve and serve as the infrastructure for carrying massive amounts of multimodal and multisensory observations. These observations capture various situations pertinent to people's needs and interests along with all their idiosyncrasies. To support human-centered computing that empower people in making better and timely decisions, we look towards computation that is inspired by human perception and cognition. Toward this goal, we discuss computing paradigms of semantic computing, cognitive computing, and an emerging aspect of computing, which we call perceptual computing. In our view, these offer a continuum to make the most out of vast, growing, and diverse data pertinent to human needs and interests. We propose details of perceptual computing characterized by interpretation and exploration operations comparable to the interleaving of bottom and top brain processing.
This article consists of two parts. First we describe semantic computing, cognitive computing, and perceptual computing to lay out distinctions while acknowledging their complementary capabilities. We then provide a conceptual overview of the newest of these three paradigms--perceptual computing. For further insights, we focus on an application scenario of asthma management converting massive, heterogeneous and multimodal (big) data into actionable information or smart data.
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Improved Answer-Set Programming Encodings for Abstract Argumentation. (arXiv:1507.06689v2 [cs.AI] UPDATED)
The design of efficient solutions for abstract argumentation problems is a crucial step towards advanced argumentation systems. One of the most prominent approaches in the literature is to use Answer-Set Programming (ASP) for this endeavor. In this paper, we present new encodings for three prominent argumentation semantics using the concept of conditional literals in disjunctions as provided by the ASP-system clingo. Our new encodings are not only more succinct than previous versions, but also outperform them on standard benchmarks.
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Mourinho says referee was 'weak' after Champs League draw
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Orioles: RHP Vance Worley claimed off waivers from Pirates; RHP Jorge Rondon designated for assignment (ESPN)
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Olympiakos beats Dinamo Zagreb 1-0 in Champions League
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Valencia edges Gent 2-1 with 2 own goals
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FC Porto beats Maccabi Tel-Aviv 2-0 in Group G
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Zenit maintains 100 percent CL record with 3-1 win over Lyon
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Neymar sets up Rakitic as Barca wins 2-0 at BATE
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FIFA official: Blatter-Platini 'conflict of interest' on pay
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Ravens: Baltimore (1-5) drops 5 spots to No. 28 in Week 7 power rankings following loss to 49ers; open for full rankings (ESPN)
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Here's How SIEM Can Protect Your Privileged Accounts in the Enterprise
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Quotes from voters in this week's AP Global Football 10
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I have a new follower on Twitter
John Rampton
Entrepreneur, Investor & Connector. Founder of @Due. I blog about my journey to success. Columnist for @Entrepreneur, @TechCrunch, @Forbes and @Inc.
Palo Alto, CA
http://t.co/pZ0FhVnyIA
Following: 280475 - Followers: 278189
October 20, 2015 at 12:55PM via Twitter http://twitter.com/johnrampton
Anonymous Feedback
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Conte hearing in match-fixing scandal set for Feb. 18
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Neymar leads AP Global Football 10 after 4-goal game
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ISS Daily Summary Report – 10/19/15
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Getting Rid Of Anonymous Classes
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Google Makes Full-Disk Encryption Mandatory for New Android 6.0 Devices
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More than 250 iOS Apps Caught Using Private APIs to Collect Users' Private Data
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This Malware Can Delete and Replace Your Entire Chrome Browser with a lookalike
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High school Student Hacked Into CIA Director's Personal Email Account
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FIFA names 23-player shortlist for Ballon d'OR
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FIFA names 23-player shortlist for Ballon d'OR
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Self-belief helps young SKoreans down Brazil in U-17 upset
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Anonymous John
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Show responsive adsense in PHP only to anonymous users
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The Southern Cross in a Southern Sky
Monday, October 19, 2015
I have a new follower on Twitter
Allan Martin
Investor in #Banks, #Insurance Companies, #Startups, Entrepreneur #Fintech #Medtech #Bigdata #AI. #Pitch@amci360.com.
Tampa, Florida USA
http://t.co/L4xKC5mpFH
Following: 3789 - Followers: 4776
October 19, 2015 at 10:00PM via Twitter http://twitter.com/tampabanker
Causal Falling Rule Lists. (arXiv:1510.05189v1 [cs.AI])
A causal falling rule list (CFRL) is a sequence of if-then rules that specifies heterogeneous treatment effects, where (i) the order of rules determines the treatment effect subgroup a subject belongs to, and (ii) the treatment effect decreases monotonically down the list. A given CFRL parameterizes a hierarchical bayesian regression model in which the treatment effects are incorporated as parameters, and assumed constant within model-specific subgroups. We formulate the search for the CFRL best supported by the data as a Bayesian model selection problem, where we perform a search over the space of CFRL models, and approximate the evidence for a given CFRL model using standard variational techniques. We apply CFRL to a census wage dataset to identify subgroups of differing wage inequalities between men and women.
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System Descriptions of the First International Competition on Computational Models of Argumentation (ICCMA'15). (arXiv:1510.05373v1 [cs.AI])
This volume contains the system description of the 18 solvers submitted to the First International Competition on Computational Models of Argumentation (ICCMA'15) and therefore gives an overview on state-of-the-art of computational approaches to abstract argumentation problems. Further information on the results of the competition and the performance of the individual solvers can be found on at this http URL
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On the Computability of AIXI. (arXiv:1510.05572v1 [cs.AI])
How could we solve the machine learning and the artificial intelligence problem if we had infinite computation? Solomonoff induction and the reinforcement learning agent AIXI are proposed answers to this question. Both are known to be incomputable. In this paper, we quantify this using the arithmetical hierarchy, and prove upper and corresponding lower bounds for incomputability. We show that AIXI is not limit computable, thus it cannot be approximated using finite computation. Our main result is a limit-computable {\epsilon}-optimal version of AIXI with infinite horizon that maximizes expected rewards.
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PERCH: Perception via Search for Multi-Object Recognition and Localization. (arXiv:1510.05613v1 [cs.CV])
In many robotic domains such as flexible automated manufacturing or personal assistance, a fundamental perception task is that of identifying and localizing objects whose 3D models are known. Canonical approaches to this problem include discriminative methods that find correspondences between feature descriptors computed over the model and observed data. While these methods have been employed successfully, they can be unreliable when the feature descriptors cannot capture variations in observed data: a classic example being occlusion. As a step towards deliberative reasoning, we present PERCH: PErception via SeaRCH, an algorithm that seeks to find the best explanation of the observed sensor data by hypothesizing possible scenes in a generative fashion. Our contributions are: i) formulating the multi-object recognition and localization task as an optimization problem over the space of hypothesized scenes, ii) exploiting structure in the optimization to cast it as a combinatorial search problem on what we call the Monotone Scene Generation Tree, and iii) leveraging parallelization and recent advances in multi-heuristic search in making combinatorial search tractable. We prove that our system can guaranteeably produce the best explanation of the scene under the chosen cost function, and validate our claims on real world RGB-D test data. Our experimental results show that we can identify and localize objects under heavy occlusion--cases where state-of-the-art methods struggle.
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The Limitations of Standardized Science Tests as Benchmarks for Artificial Intelligence Research: Position Paper. (arXiv:1411.1629v2 [cs.AI] UPDATED)
In this position paper, I argue that standardized tests for elementary science such as SAT or Regents tests are not very good benchmarks for measuring the progress of artificial intelligence systems in understanding basic science. The primary problem is that these tests are designed to test aspects of knowledge and ability that are challenging for people; the aspects that are challenging for AI systems are very different. In particular, standardized tests do not test knowledge that is obvious for people; none of this knowledge can be assumed in AI systems. Individual standardized tests also have specific features that are not necessarily appropriate for an AI benchmark. I analyze the Physics subject SAT in some detail and the New York State Regents Science test more briefly. I also argue that the apparent advantages offered by using standardized tests are mostly either minor or illusory. The one major real advantage is that the significance is easily explained to the public; but I argue that even this is a somewhat mixed blessing. I conclude by arguing that, first, more appropriate collections of exam style problems could be assembled, and second, that there are better kinds of benchmarks than exam-style problems. In an appendix I present a collection of sample exam-style problems that test kinds of knowledge missing from the standardized tests.
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On the Computability of Solomonoff Induction and Knowledge-Seeking. (arXiv:1507.04124v1 [cs.AI] CROSS LISTED)
Solomonoff induction is held as a gold standard for learning, but it is known to be incomputable. We quantify its incomputability by placing various flavors of Solomonoff's prior M in the arithmetical hierarchy. We also derive computability bounds for knowledge-seeking agents, and give a limit-computable weakly asymptotically optimal reinforcement learning agent.
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[FD] Firefox FindMyDevice Critical ClickJacking Security Vulnerability
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[FD] Seagate Central NAS vulnerabilities
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[FD] Western Digital - My Passport / My Book self-encrypting external hard drive series - Multiple vulnerabilities
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