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Saturday, November 28, 2015
Make Anonymous Grading notification in Grades section a Feature Option
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I have a new follower on Twitter
Marcus Biel
Software Craftsman, Trainer, Speaker, Clean Code Activist, Java addict. #refugeeswelcome
Munich, Germany
https://t.co/ozscglwSVn
Following: 3010 - Followers: 12034
November 28, 2015 at 10:27AM via Twitter http://twitter.com/MarcusBiel
[FD] Visual Paradigm Server v10.0 - Cross Site Scripting (XSS)
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Re: [FD] Google Translator affected by Cross-Site Scripting vulnerability
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Gravity's Grin
Friday, November 27, 2015
Anonymous white
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CDN distribution does an anonymous define in AMD environments, causing errors
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Anonymous: 'Sto core mio se fusse de diamante
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I have a new follower on Twitter
MyNewNFLJerseyfetish
The three bird mascots of the Baltimore Ravens are named Edgar, Allan and Poe. Tap the Hyperlink below to get your favored NFL Jersey This Second.
Angleton, TX
https://t.co/60zkfE6Knq
Following: 2752 - Followers: 1017
November 27, 2015 at 02:08PM via Twitter http://twitter.com/MyNewNFLJersey
I have a new follower on Twitter
FredLandis
Cloud Alliance Marketer and Strategist
http://t.co/SNVDzhMM4N
Following: 6529 - Followers: 7428
November 27, 2015 at 01:06PM via Twitter http://twitter.com/flandis
I have a new follower on Twitter
Thom Wall
Former geek enabler, but now realised am infact a Geek! Replica Prop & Costume Artist, Cosplayer, Events Organizer, Cat and Dinosaur enthusiast.
Glasgow
http://t.co/sUVolCoO3T
Following: 3008 - Followers: 4952
November 27, 2015 at 01:06PM via Twitter http://twitter.com/SorenzoProps
Ravens: A lot has changed since Dec. 30, 2007, the last time a QB not named Joe Flacco started for Baltimore - Hensley (ESPN)
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Anonymous jobs
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Millions of IoT Devices Using Same Hard-Coded CRYPTO Keys
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ISS Daily Summary Report – 11/25/15
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Critical 'Port Fail' Vulnerability Reveals Real IP Addresses of VPN Users
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[FD] PRTG Network Monitor Tool – Multiple Cross-Site Scripting Vulnerability
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ISIS page hacked, replaced with Viagra ad. Anonymous group hopes Islamic State will rise up and ...
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[FD] [CVE-2015-6942] CoreMail XT3.0 Stored XSS
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[FD] Google Translator affected by Cross-Site Scripting vulnerability
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How to Root Windows Phone and Unlock the Bootloader to Install Custom ROMs
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Planets of the Morning
Thursday, November 26, 2015
'Swede' Hanson impacted thousands of lives but stayed largely anonymous
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Ocean City, MD's surf is at least 5.32ft high
Ocean City, MD Summary
At 2:00 AM, surf min of 4.92ft. At 8:00 AM, surf min of 5.32ft. At 2:00 PM, surf min of 3.2ft. At 8:00 PM, surf min of 3.28ft.
Surf maximum: 5.78ft (1.76m)
Surf minimum: 5.32ft (1.62m)
Tide height: 1.62ft (0.49m)
Wind direction: ESE
Wind speed: 9.17 KTS
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Anonymous Reporting
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Live at Santas Anonymous 3
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Anonymous hacks Isis, replaces propaganda with drugs ads
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Li-Fi is 100 times Faster than Wi-Fi Technology: Real-World Tests Prove
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Raspberry Pi Zero — The $5 Tiny Computer is Here
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Hackers are using Nuclear Exploit Kit to Spread Cryptowall 4.0 Ransomware
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Mr. Grey Hacker (Wanted by FBI) Steals 1.2 BILLION Login Passwords
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Unusual Pits Discovered on Pluto
Wednesday, November 25, 2015
Live at Santas Anonymous 2
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I have a new follower on Twitter
Shinedowns Nation
Shinedowns Nation - A @Shinedown Fan Page. New album 'Threat To Survival' is out now! Get your copy here: https://t.co/uHsbb4qPYZ
Shinedown Nation
http://t.co/rS31qutFo0
Following: 117126 - Followers: 115226
November 25, 2015 at 11:52PM via Twitter http://twitter.com/Shinedown_Fans
Learning with Memory Embeddings. (arXiv:1511.07972v1 [cs.AI])
Embedding learning, a.k.a. representation learning, has been shown to be able to model large-scale semantic knowledge graphs. A key concept is a mapping of the knowledge graph to a tensor representation whose entries are predicted by models using latent representations of generalized entities. In recent publications the embedding models were extended to also consider temporal evolutions, temporal patterns and subsymbolic representations. These extended models were used successfully to predict clinical events like procedures, lab measurements, and diagnoses. In this paper, we attempt to map these embedding models, which were developed purely as solutions to technical problems, to various cognitive memory functions, in particular to semantic and concept memory, episodic memory and sensory memory. We also make an analogy between a predictive model, which uses entity representations derived in memory models, to working memory. Cognitive memory functions are typically classified as long-term or short-term memory, where long-term memory has the subcategories declarative memory and non-declarative memory and the short term memory has the subcategories sensory memory and working memory. There is evidence that these main cognitive categories are partially dissociated from one another in the brain, as expressed in their differential sensitivity to brain damage. However, there is also evidence indicating that the different memory functions are not mutually independent. A hypothesis that arises out off this work is that mutual information exchange can be achieved by sharing or coupling of distributed latent representations of entities across different memory functions.
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Strategic Dialogue Management via Deep Reinforcement Learning. (arXiv:1511.08099v1 [cs.AI])
Artificially intelligent agents equipped with strategic skills that can negotiate during their interactions with other natural or artificial agents are still underdeveloped. This paper describes a successful application of Deep Reinforcement Learning (DRL) for training intelligent agents with strategic conversational skills, in a situated dialogue setting. Previous studies have modelled the behaviour of strategic agents using supervised learning and traditional reinforcement learning techniques, the latter using tabular representations or learning with linear function approximation. In this study, we apply DRL with a high-dimensional state space to the strategic board game of Settlers of Catan---where players can offer resources in exchange for others and they can also reply to offers made by other players. Our experimental results report that the DRL-based learnt policies significantly outperformed several baselines including random, rule-based, and supervised-based behaviours. The DRL-based policy has a 53% win rate versus 3 automated players (`bots'), whereas a supervised player trained on a dialogue corpus in this setting achieved only 27%, versus the same 3 bots. This result supports the claim that DRL is a promising framework for training dialogue systems, and strategic agents with negotiation abilities.
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A Roadmap towards Machine Intelligence. (arXiv:1511.08130v1 [cs.AI])
The development of intelligent machines is one of the biggest unsolved challenges in computer science. In this paper, we propose some fundamental properties these machines should have, focusing in particular on communication and learning. We discuss a simple environment that could be used to incrementally teach a machine the basics of natural-language-based communication, as a prerequisite to more complex interaction with human users. We also present some conjectures on the sort of algorithms the machine should support in order to profitably learn from the environment.
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Improving Decision Trees Using Tsallis Entropy. (arXiv:1511.08136v1 [stat.ML])
The construction of efficient and effective decision trees remains a key topic in machine learning because of their simplicity and flexibility. A lot of heuristic algorithms have been proposed to construct near-optimal decision trees. Most of them, however, are greedy algorithms which have the drawback of obtaining only local optimums. Besides, common split criteria, e.g. Shannon entropy, Gain Ratio and Gini index, are also not flexible due to lack of adjustable parameters on data sets. To address the above issues, we propose a series of novel methods using Tsallis entropy in this paper. Firstly, a Tsallis Entropy Criterion (TEC) algorithm is proposed to unify Shannon entropy, Gain Ratio and Gini index, which generalizes the split criteria of decision trees. Secondly, we propose a Tsallis Entropy Information Metric (TEIM) algorithm for efficient construction of decision trees. The TEIM algorithm takes advantages of the adaptability of Tsallis conditional entropy and the reducing greediness ability of two-stage approach. Experimental results on UCI data sets indicate that the TEC algorithm achieves statistically significant improvement over the classical algorithms, and that the TEIM algorithm yields significantly better decision trees in both classification accuracy and tree complexity.
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Plan Explainability and Predictability for Cobots. (arXiv:1511.08158v1 [cs.AI])
Robots are becoming pervasive in human populated environments. A desirable capability of these robots (cobots) is to respond to goal-oriented commands by autonomously constructing plans. However, such autonomy can add significant cognitive load and even potentially introduce safety risks to the humans when robots choose their plans unexpectedly. As a result, for cobots to be more helpful, one important requirement is for them to synthesize plans that do not {\it surprise} the humans. While there are previous works that studied socially acceptable robots which discuss ``natural ways'' for cobots to interact with humans, there still lacks a general solution, especially for cobots that can construct their own plans. In this paper, we introduce the notions of plan {\it explainability} and {\it predictability}. To compute these measures, first, we postulate that humans understand robot plans by associating high level tasks with robot actions, which can be considered as a labeling process. We learn the labeling scheme of humans for robot plans from training examples using conditional random fields (CRFs). Then, we use the learned model to label a new plan to compute its explainability and predictability. These measures can be used by cobots to proactively choose plans, or directly incorporated into the planning process to generate plans that are more explainable and predictable. We provide an evaluation on a synthetic dataset to demonstrate the effectiveness of our approach.
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Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models. (arXiv:1507.04808v2 [cs.CL] UPDATED)
We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses that are autonomously generated word-by-word, opening up the possibility for realistic, flexible interactions. In support of this goal, we extend the recently proposed hierarchical recurrent encoder-decoder neural network to the dialogue domain, and demonstrate that this model is competitive with state-of-the-art neural language models and back-off n-gram models. We investigate the limitations of this and similar approaches, and show how its performance can be improved by bootstrapping the learning from a larger question-answer pair corpus and from pretrained word embeddings.
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Identification by Auxiliary Instrumental Sets in Linear Structural Equation Models. (arXiv:1511.02995v2 [stat.ME] CROSS LISTED)
We extend graph-based identification methods for linear models by allowing background knowledge in the form of externally evaluated parameters. Such information could be obtained, for example, from a previously conducted randomized experiment, from substantive understanding of the domain, or even from another identification technique. To incorporate such information systematically, we propose the addition of auxiliary variables to the model, which are constructed so that certain paths will be conveniently cancelled. This cancellation allows the auxiliary variables to help conventional methods of identification (e.g., single-door criterion, instrumental variables, half-trek criterion) and model testing (e.g., d-separation, over-identification). Moreover, by iteratively alternating steps of identification and adding auxiliary variables, we can improve the power of existing identification and model testing methods, even without additional knowledge. We operationalize this general approach for instrumental sets (a generalization of instrumental variables) and show that the resulting procedure subsumes the most general identification method for linear systems known to date. We further discuss the application of this new operation in the tasks of model testing and z-identification.
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[anonymous_publishing] Anonymous publishing
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Anonymous resident pays for firefighters' groceries
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I have a new follower on Twitter
RANN
Brooklyn, NY
https://t.co/tgpQ1hGX6R
Following: 3915 - Followers: 3118
November 25, 2015 at 02:25PM via Twitter http://twitter.com/rannpage
"Anonymous" Could Derail Government Attempts to Target ISIS
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Chile FF president in Miami after resigning amid FIFA probe
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[FD] CIS Manager Content Management System 2015Q4 - SQL Injection Vulnerability
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Anonymous declares cyber war on ISIS
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Russian ATM Hackers Steal $4 Million in Cash with 'Reverse ATM Hack' Technique
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ISS Daily Summary Report – 11/24/15
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I have a new follower on Twitter
Autokids
Позаботьтесь о безопасности и комфорте Вашего ребенка вместе с http://t.co/nqbKcYYTkE – лучшим интернет-магазином детских автокресел в Украине!
http://t.co/9YAM86YyEO
Following: 2398 - Followers: 2147
November 25, 2015 at 08:16AM via Twitter http://twitter.com/AutokidsUA
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Gorde Center
Following: 1232 - Followers: 1008
November 25, 2015 at 07:58AM via Twitter http://twitter.com/GordeSchool
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eatme
Ресторанный портал eatme.ua – лучший ресторанный портал, который всегда знает, чего Вы хотите.
Киев
http://t.co/w6Ws4K2WU7
Following: 2295 - Followers: 2071
November 25, 2015 at 07:45AM via Twitter http://twitter.com/eatmeua
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cloudnews☁️
Today's Paper: Pictures, Videos, Latest Breaking Worldwide News
EU / US / Worldwide
https://t.co/tBqhN3ueaJ
Following: 4839 - Followers: 4673
November 25, 2015 at 07:27AM via Twitter http://twitter.com/ambassadorua
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DomSporta
DomSporta является профессиональным магазином по продаже спортивного оборудования и товаров для активного отдыха.
Киев
http://t.co/1B8SjXoTaT
Following: 3442 - Followers: 2862
November 25, 2015 at 07:12AM via Twitter http://twitter.com/DomSportaua
This $10 Device Can Guess and Steal Your Next Credit Card Number before You've Received It
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OZON
The 1st all-in-one #Cybersecurity Solution designed for #eCommerce SMB. Full and immediate protection against hackers & fraudsters.
Worldwide
http://t.co/KUgvU0NDf6
Following: 1535 - Followers: 1447
November 25, 2015 at 04:45AM via Twitter http://twitter.com/ozon_io
I have a new follower on Twitter
Paw Kyhl Jensen
This is for the people who wants to follow the progress of developing TimeXtender.
Denmark
http://t.co/dVI6cS2a8U
Following: 1243 - Followers: 1206
November 25, 2015 at 04:21AM via Twitter http://twitter.com/pawkyhljensen
[FD] Celoxis <= 9.5 - Cross Site Scripting (XSS)
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[FD] [ERPSCAN-15-019] SAP Afaria - Stored XSS
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Scott J. Weaver, Sr.
Consulting Firm that grows Business income via Web Design SEM SMM EM Marketing sched free call via - https://t.co/1pjmwqHzrg
Midwest
https://t.co/KHJ6A89MiH
Following: 1179 - Followers: 1497
November 25, 2015 at 02:10AM via Twitter http://twitter.com/SJWeaverMARKTNG
[FD] Leak information on Huawei HG253s v2, Comtrend VG 8050 and ADB P.DGA4001N (HomeStation)
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Re: [FD] LiteCart 1.3.2: Multiple XSS
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[FD] Cross Site Scripting (XSS) 0day in SimpleViewer all versions
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[FD] : CVE-2015-8298 SQL Injection Vulnerability in RXTEC RXAdmin
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[FD] : CVE-2015-8299 RCE Vulnerability in the KNX management software ETS
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[FD] CVE-2015-8300: Polycom BToE Connector v2.3.0 Privilege Escalation Vulnerability
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Personal spaces are no longer linked and creator is anonymous
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Will Anonymous's war on ISIS have any effect?
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Aurora over Clouds
The Lowdown on Anonymous
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"Anonymous" Needs Oversight, Coordination to Pose Real Threat
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thebenevolentone3
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Anonymous vs ISIS, Australian attorney general, NTP and DDoS exploits
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Tuesday, November 24, 2015
A Survey of Signed Network Mining in Social Media. (arXiv:1511.07569v1 [cs.SI])
Many real-world relations can be represented by signed networks with positive and negative links, and signed network analysis has attracted increasing attention from multiple disciplines. With the evolution of data from offline to social media networks, signed network analysis has evolved from developing and measuring theories to mining tasks. In this article, we present a review of mining signed networks in social media and discuss some promising research directions and new frontiers. We begin by giving basic concepts and unique properties and principles of signed networks. Then we classify and review tasks of signed network mining with representative algorithms. We also delineate some tasks that have not been extensively studied with formal definitions and research directions to expand the boundaries of signed network mining.
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Approximate Probabilistic Inference via Word-Level Counting. (arXiv:1511.07663v1 [cs.AI])
Hashing-based model counting has emerged as a promising approach for large-scale probabilistic inference on graphical models. A key component of these techniques is the use of xor-based 2-universal hash functions that operate over Boolean domains. Many counting problems arising in probabilistic inference are, however, naturally encoded over finite discrete domains. Techniques based on bit-level (or Boolean) hash functions require these problems to be propositionalized, making it impossible to leverage the remarkable progress made in SMT (Satisfiability Modulo Theory) solvers that can reason directly over words (or bit-vectors). In this work, we present the first approximate model counter that uses word-level hashing functions, and can directly leverage the power of sophisticated SMT solvers. Empirical evaluation over an extensive suite of benchmarks demonstrates the promise of the approach.
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Searching for Objects using Structure in Indoor Scenes. (arXiv:1511.07710v1 [cs.CV])
To identify the location of objects of a particular class, a passive computer vision system generally processes all the regions in an image to finally output few regions. However, we can use structure in the scene to search for objects without processing the entire image. We propose a search technique that sequentially processes image regions such that the regions that are more likely to correspond to the query class object are explored earlier. We frame the problem as a Markov decision process and use an imitation learning algorithm to learn a search strategy. Since structure in the scene is essential for search, we work with indoor scene images as they contain both unary scene context information and object-object context in the scene. We perform experiments on the NYU-depth v2 dataset and show that the unary scene context features alone can achieve a significantly high average precision while processing only 20-25\% of the regions for classes like bed and sofa. By considering object-object context along with the scene context features, the performance is further improved for classes like counter, lamp, pillow and sofa.
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Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions. (arXiv:1410.7827v2 [cs.LG] UPDATED)
In this work, we propose a generalized product of experts (gPoE) framework for combining the predictions of multiple probabilistic models. We identify four desirable properties that are important for scalability, expressiveness and robustness, when learning and inferring with a combination of multiple models. Through analysis and experiments, we show that gPoE of Gaussian processes (GP) have these qualities, while no other existing combination schemes satisfy all of them at the same time. The resulting GP-gPoE is highly scalable as individual GP experts can be independently learned in parallel; very expressive as the way experts are combined depends on the input rather than fixed; the combined prediction is still a valid probabilistic model with natural interpretation; and finally robust to unreliable predictions from individual experts.
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Context-Aware Bandits. (arXiv:1510.03164v2 [cs.LG] UPDATED)
In this paper, we present a simple and efficient Context-Aware Bandit (CAB) algorithm. With CAB we attempt to craft a bandit algorithm that can capture collaborative effects and that can be easily deployed in a real-world recommendation system, where the multi-armed bandits have been shown to perform well in particular with respect to the cold-start problem. CAB utilizes a context-aware clustering technique augmenting exploration-exploitation strategies. CAB dynamically clusters the users based on the content universe under consideration. We provide a theoretical analysis in the standard stochastic multi-armed bandits setting. We demonstrate the efficiency of our approach on production and real-world datasets, showing the scalability and, more importantly, the significantly increased prediction performance against several existing state-of-the-art methods.
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Ravens: QB Jimmy Clausen claimed off waivers, worked with OC Marc Trestman in Chicago in 2014; Joe Flacco placed on IR (ESPN)
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I have a new follower on Twitter
software video
Software per Video editing, codec, rip
Italy
http://t.co/iyXrcyGSPV
Following: 3503 - Followers: 1066
November 24, 2015 at 03:25PM via Twitter http://twitter.com/software_video
Ravens: Baltimore (3-7) drops 1 spot to No. 30 in Week 12 NFL power rankings; open here for full rankings (ESPN)
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Maria Gonzalo
I am a sweet girl who love men and I enjoy it when I am looked after and given flowers. I love romantic walks under the moon and night swimming naked.
Following: 790 - Followers: 104
November 24, 2015 at 01:08PM via Twitter http://twitter.com/MariaGonzal21
Boston Briefing: Pats lose two more WRs; Danny Ainge talks Celts' season; Hanley Ramirez's winter plan; Bruins win in SO (ESPN)
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[FD] List of Bug Bounty Programs INTERNATIONAL 427+ OFFICIAL - Bug Bounty Sheet
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I have a new follower on Twitter
Louise Webster
Following: 408 - Followers: 111
November 24, 2015 at 07:29AM via Twitter http://twitter.com/LouiseWebster22
ISS Daily Summary Report – 11/23/15
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Sara Calderon
Following: 336 - Followers: 59
November 24, 2015 at 07:23AM via Twitter http://twitter.com/Sara19Calderon
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Betty Young
Following: 821 - Followers: 123
November 24, 2015 at 07:18AM via Twitter http://twitter.com/Betty4Young
Hacker Claims He helped FBI Track Down ISIS Hacker (Who was killed in Drone-Strike)
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Norma Jones
Following: 387 - Followers: 108
November 24, 2015 at 07:05AM via Twitter http://twitter.com/NormaJones21
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Eleana García
Following: 397 - Followers: 104
November 24, 2015 at 07:05AM via Twitter http://twitter.com/GarciaEleana20
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Kathy Youmans
Following: 345 - Followers: 90
November 24, 2015 at 06:59AM via Twitter http://twitter.com/KathyYoumans21
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Gloria Boolman
Following: 395 - Followers: 118
November 24, 2015 at 06:59AM via Twitter http://twitter.com/BoolmanGloria
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Holly Gerald
Following: 421 - Followers: 98
November 24, 2015 at 06:45AM via Twitter http://twitter.com/HollyGerald
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Paris Gilmore
Following: 673 - Followers: 87
November 24, 2015 at 06:33AM via Twitter http://twitter.com/ParisGilmore21
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Susan Dyson
Following: 405 - Followers: 103
November 24, 2015 at 06:33AM via Twitter http://twitter.com/Susan21Dyson