COLT 2013 - Princeton

26th Annual Conference on Learning Theory (COLT), Princeton 2013

The conference is a single track meeting that includes invited talks as well as oral presentations of all refereed papers. We invited submissions of papers addressing theoretical aspects of machine learning and related topics. We strongly support a broad definition of learning theory, including, but not limited to:

Design and analysis of learning algorithms and their generalization ability
Computational complexity of learning
Optimization procedures for learning
Unsupervised, semi-supervised learning and clustering
Online learning
Active learning
High dimensional and non-parametric empirical inference, including sparsity methods
Planning and control, including reinforcement learning
Learning with additional constraints: E.g. privacy, time or memory budget, communication
Learning in other settings: E.g. social, economic, and game-theoretic
Analysis of learning in related fields: natural language processing, neuroscience, bioinformatics, privacy and security, machine vision, data mining, information retrieval.

For more information visit the COLT 2013 website.

Categories

Top » Computer Science » Machine Learning » Reinforcement Learning
Top » Computer Science » Machine Learning » Active Learning
Top » Computer Science » Machine Learning » Computational Learning Theory
Top » Computer Science » Machine Learning » On-line Learning
Top » Computer Science » Machine Learning » Semi-supervised Learning


Invited Talks
[syn] 3160 views, 54:32 Invited Talk Learning Representations: A Challenge for Learning TheoryLearning Representations: A Challenge for Learning Theory Yann LeCun Yann LeCun	[syn] 369 views, 52:15 Invited Talk Is Intractability a Barrier for Machine Learning?Is Intractability a Barrier for Machine Learning? Sanjeev Arora Sanjeev Arora
Online Learning (I)
[syn] 377 views, 21:07 Online Learning for Time Series PredictionOnline Learning for Time Series Prediction Elad Hazan Elad Hazan	[syn] 42 views, 18:23 A Tale of Two Metrics: Simultaneous Bounds on Competitiveness and RegretA Tale of Two Metrics: Simultaneous Bounds on Competitiveness and ... Siddharth Barman Siddharth Barman	[syn] 92 views, 19:43 Competing With StrategiesCompeting With Strategies Karthik Sridharan Karthik Sridharan	[syn] 107 views, 05:33 Online Learning with Predictable SequencesOnline Learning with Predictable Sequences Alexander Rakhlin Alexander Rakhlin	[syn] 39 views, 05:29 Approachability, fast and slowApproachability, fast and slow Vianney Perchet Vianney Perchet
[syn] 300 views, 05:33 Horizon-Independent Optimal Prediction with Log-Loss in Exponential FamiliesHorizon-Independent Optimal Prediction with Log-Loss in Exponential Families Fares Hedayati Fares Hedayati
Online Learning (II)
[syn] 46 views, 21:02 Opportunistic Strategies for Generalized No-Regret ProblemsOpportunistic Strategies for Generalized No-Regret Problems Andrey Bernstein Andrey Bernstein	[syn] 91 views, 16:40 Prediction by random-walk perturbationPrediction by random-walk perturbation Gergely Neu Gergely Neu	[syn] 58 views, 18:32 Online Similarity Prediction of Networked Data from Known and Unknown GraphsOnline Similarity Prediction of Networked Data from Known and Unknown ... Mark Herbster Mark Herbster
Computational Learning Theory (I)
[syn] 475 views, 20:38 Best Paper Complexity Theoretic Lower Bounds for Sparse Principal Component DetectionComplexity Theoretic Lower Bounds for Sparse Principal Component Detection Quentin Berthet Quentin Berthet 1 comment	[syn] 65 views, 22:03 Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment MatchingLearning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching Raghu Meka Raghu Meka
Computational Learning Theory (II)
[syn] 60 views, 20:35 Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision TreesRepresentation, Approximation and Learning of Submodular Functions Using Low-rank Decision ... Pravesh Kothari Pravesh Kothari	[syn] 93 views, 21:02 Algorithms and Hardness for Robust Subspace RecoveryAlgorithms and Hardness for Robust Subspace Recovery Moritz Hardt Moritz Hardt
Computational Learning Theory (III)
[syn] 58 views, 20:50 Efficient Learning of SimplicesEfficient Learning of Simplices Luis Rademacher Luis Rademacher	[syn] 161 views, 21:45 Randomized partition trees for exact nearest neighbor searchRandomized partition trees for exact nearest neighbor search Sanjoy Dasgupta Sanjoy Dasgupta
Unsupervised Learning
[syn] 114 views, 18:41 A Tensor Spectral Approach to Learning Mixed Membership Community ModelsA Tensor Spectral Approach to Learning Mixed Membership Community Models Rong Ge Rong Ge	[syn] 73 views, 18:50 Optimal Probability Estimation with Applications to Prediction and ClassificationOptimal Probability Estimation with Applications to Prediction and Classification Ananda Theertha Suresh Ananda Theertha Suresh	[syn] 105 views, 18:23 Blind Signal Separation in the Presence of Gaussian NoiseBlind Signal Separation in the Presence of Gaussian Noise James Voss James Voss	[syn] 55 views, 05:43 Learning a set of directionsLearning a set of directions Wouter M. Koolen Wouter M. Koolen	[syn] 43 views, 05:37 Sparse Adaptive Dirichlet-Multinomial-like ProcessesSparse Adaptive Dirichlet-Multinomial-like Processes Tor Lattimore Tor Lattimore
Dimensionality Reduction and Loss Function
[syn] 63 views, 22:20 Subspace Embeddings and ℓp-Regression Using Exponential Random VariablesSubspace Embeddings and ℓp-Regression Using Exponential Random Variables Qin Zhang Qin Zhang	[syn] 110 views, 19:59 Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper LossesSurrogate Regret Bounds for the Area Under the ROC Curve ... Shivani Agarwal Shivani Agarwal	[syn] 72 views, 06:17 A Theoretical Analysis of NDCG Type Ranking MeasuresA Theoretical Analysis of NDCG Type Ranking Measures Liwei Wang Liwei Wang
Statistical Learning Theory (I)
[syn] 52 views, 13:14 Passive Learning with Target RiskPassive Learning with Target Risk Mehrdad Mahdavi Mehrdad Mahdavi	[syn] 55 views, 19:36 Classification with Asymmetric Label Noise: Consistency and Maximal DenoisingClassification with Asymmetric Label Noise: Consistency and Maximal Denoising Gilles Blanchard Gilles Blanchard	[syn] 146 views, 18:02 Divide and Conquer Kernel Ridge RegressionDivide and Conquer Kernel Ridge Regression Yuchen Zhang Yuchen Zhang	[syn] 101 views, 05:28 Sharp analysis of low-rank kernel matrix approximationsSharp analysis of low-rank kernel matrix approximations Francis R. Bach Francis R. Bach	[syn] 66 views, 04:21 Consistency of Robust Kernel Density EstimatorsConsistency of Robust Kernel Density Estimators Robert A. Vandermeulen Robert A. Vandermeulen
[syn] 1 view, 04:58 Excess risk bounds for multitask learning with trace norm regularizationExcess risk bounds for multitask learning with trace norm regularization Massimiliano Pontil Massimiliano Pontil	[syn] 34 views, 05:27 General Oracle Inequalities for Gibbs Posterior with Application to RankingGeneral Oracle Inequalities for Gibbs Posterior with Application to Ranking Cheng Li Cheng Li	[syn] 90 views, 05:00 Boosting with the Logistic Loss is ConsistentBoosting with the Logistic Loss is Consistent Matus Telgarsky Matus Telgarsky
Statistical Learning Theory (II)
[syn] 113 views, 19:27 Mark Fulk Award Honest Compressions and Their Application to Compression SchemesHonest Compressions and Their Application to Compression Schemes Roi Livni Roi Livni	[syn] 57 views, 19:11 Differentially Private Feature Selection via Stability Arguments, and the Robustness of the LassoDifferentially Private Feature Selection via Stability Arguments, and the Robustness ... Abhradeep Guha Thakurta Abhradeep Guha Thakurta
Active Learning
[syn] 64 views, 18:54 Best Student Paper Learning Using Local Membership QueriesLearning Using Local Membership Queries Pranjal Awasthi Pranjal Awasthi	[syn] 107 views, 18:32 PLAL: Cluster-based active learningPLAL: Cluster-based active learning Ruth Urner Ruth Urner	[syn] 38 views, 19:58 Estimation of Extreme Values and Associated Level Sets of a Regression Function via Selective SamplingEstimation of Extreme Values and Associated Level Sets of a ... Stanislav Minsker Stanislav Minsker	[syn] 445 views, 22:58 Active and passive learning of linear separators under log-concave distributionsActive and passive learning of linear separators under log-concave distributions Maria-Florina Balcan Maria-Florina Balcan	[syn] 52 views, 16:08 On the Complexity of Bandit and Derivative-Free Stochastic Convex OptimizationOn the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization Ohad Shamir Ohad Shamir
Bandits
[syn] 33 views, 16:08 The price of bandit information in multiclass online classificationThe price of bandit information in multiclass online classification Amit Daniely Amit Daniely	[syn] 201 views, 23:14 Bounded regret in stochastic multi-armed banditsBounded regret in stochastic multi-armed bandits Sébastien Bubeck Sébastien Bubeck	[syn] 55 views, 19:55 Beating Bandits in Gradually Evolving WorldsBeating Bandits in Gradually Evolving Worlds Chia-Jung Lee Chia-Jung Lee	[syn] 64 views, 05:56 Information Complexity in Bandit Subset SelectionInformation Complexity in Bandit Subset Selection Emilie Kaufmann Emilie Kaufmann	[syn] 25 views, 06:13 A near-optimal algorithm for finite partial-monitoring games against adversarial opponentsA near-optimal algorithm for finite partial-monitoring games against adversarial opponents Gábor Bartók Gábor Bartók
[syn] 42 views, 08:31 Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem Aleksandrs Slivkins Aleksandrs Slivkins