Volume 30: Conference on Learning Theory, 12-14 June 2013, Princeton, NJ, USA
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Editors:
Shai Shalev-Shwartz,
Ingo Steinwart
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Preface
Preface
Shai Shalev-Shwartz,
Ingo Steinwart
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PMLR 30:1-2
[abs]
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Regular Papers
Open Problems
Open Problem: Adversarial Multiarmed Bandits with Limited Advice
Yevgeny Seldin,
Koby Crammer,
Peter Bartlett
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PMLR 30:1067-1072
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Open Problem: Fast Stochastic Exp-Concave Optimization
Tomer Koren
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PMLR 30:1073-1075
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Open Problem: Lower bounds for Boosting with Hadamard Matrices
Jiazhong Nie,
Manfred K. Warmuth,
S.V.N. Vishwanathan,
Xinhua Zhang
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PMLR 30:1076-1079
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On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Ohad Shamir
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PMLR 30:3-24
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A Theoretical Analysis of NDCG Type Ranking Measures
Yining Wang,
Liwei Wang,
Yuanzhi Li,
Di He,
Tie-Yan Liu
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PMLR 30:25-54
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Excess risk bounds for multitask learning with trace norm regularization
Massimiliano Pontil,
Andreas Maurer
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PMLR 30:55-76
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Honest Compressions and Their Application to Compression Schemes
Roi Livni,
Pierre Simon
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PMLR 30:77-92
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The price of bandit information in multiclass online classification
Amit Daniely,
Tom Helbertal
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PMLR 30:93-104
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Estimation of Extreme Values and Associated Level Sets of a Regression Function via Selective Sampling
Stanislav Minsker
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PMLR 30:105-121
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Bounded regret in stochastic multi-armed bandits
Sébastien Bubeck,
Vianney Perchet,
Philippe Rigollet
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PMLR 30:122-134
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Recovering the Optimal Solution by Dual Random Projection
Lijun Zhang,
Mehrdad Mahdavi,
Rong Jin,
Tianbao Yang,
Shenghuo Zhu
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PMLR 30:135-157
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Opportunistic Strategies for Generalized No-Regret Problems
Andrey Bernstein,
Shie Mannor,
Nahum Shimkin
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PMLR 30:158-171
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Online Learning for Time Series Prediction
Oren Anava,
Elad Hazan,
Shie Mannor,
Ohad Shamir
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PMLR 30:172-184
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Sharp analysis of low-rank kernel matrix approximations
Francis Bach
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PMLR 30:185-209
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Beating Bandits in Gradually Evolving Worlds
Chao-Kai Chiang,
Chia-Jung Lee,
Chi-Jen Lu
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PMLR 30:210-227
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Information Complexity in Bandit Subset Selection
Emilie Kaufmann,
Shivaram Kalyanakrishnan
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PMLR 30:228-251
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Passive Learning with Target Risk
Mehrdad Mahdavi,
Rong Jin
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PMLR 30:252-269
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Blind Signal Separation in the Presence of Gaussian Noise
Mikhail Belkin,
Luis Rademacher,
James Voss
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PMLR 30:270-287
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Active and passive learning of linear separators under log-concave distributions
Maria-Florina Balcan,
Phil Long
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PMLR 30:288-316
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Randomized partition trees for exact nearest neighbor search
Sanjoy Dasgupta,
Kaushik Sinha
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PMLR 30:317-337
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Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper Losses
Shivani Agarwal
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PMLR 30:338-353
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Algorithms and Hardness for Robust Subspace Recovery
Moritz Hardt,
Ankur Moitra
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PMLR 30:354-375
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PLAL: Cluster-based active learning
Ruth Urner,
Sharon Wulff,
Shai Ben-David
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PMLR 30:376-397
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Learning Using Local Membership Queries
Pranjal Awasthi,
Vitaly Feldman,
Varun Kanade
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PMLR 30:398-431
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Sparse Adaptive Dirichlet-Multinomial-like Processes
Marcus Hutter
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PMLR 30:432-459
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Prediction by random-walk perturbation
Luc Devroye,
Gábor Lugosi,
Gergely Neu
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PMLR 30:460-473
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Approachability, fast and slow
Vianney Perchet,
Shie Mannor
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PMLR 30:474-488
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Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Clayton Scott,
Gilles Blanchard,
Gregory Handy
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PMLR 30:489-511
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General Oracle Inequalities for Gibbs Posterior with Application to Ranking
Cheng Li,
Wenxin Jiang,
Martin Tanner
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PMLR 30:512-521
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Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching
Daniel Kane,
Adam Klivans,
Raghu Meka
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PMLR 30:522-545
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Subspace Embeddings and \ell_p-Regression Using Exponential Random Variables
David Woodruff,
Qin Zhang
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PMLR 30:546-567
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Consistency of Robust Kernel Density Estimators
Robert Vandermeulen,
Clayton Scott
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PMLR 30:568-591
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Divide and Conquer Kernel Ridge Regression
Yuchen Zhang,
John Duchi,
Martin Wainwright
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PMLR 30:592-617
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Regret Minimization for Branching Experts
Eyal Gofer,
Nicolò Cesa-Bianchi,
Claudio Gentile,
Yishay Mansour
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PMLR 30:618-638
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Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
Peter Bartlett,
Peter Grünwald,
Peter Harremoës,
Fares Hedayati,
Wojciech Kotlowski
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PMLR 30:639-661
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Online Similarity Prediction of Networked Data from Known and Unknown Graphs
Claudio Gentile,
Mark Herbster,
Stephen Pasteris
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PMLR 30:662-695
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A near-optimal algorithm for finite partial-monitoring games against adversarial opponents
Gábor Bartók
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PMLR 30:696-710
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Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees
Vitaly Feldman,
Pravesh Kothari,
Jan Vondrák
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PMLR 30:711-740
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A Tale of Two Metrics: Simultaneous Bounds on Competitiveness and Regret
Lachlan Andrew,
Siddharth Barman,
Katrina Ligett,
Minghong Lin,
Adam Meyerson,
Alan Roytman,
Adam Wierman
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PMLR 30:741-763
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Optimal Probability Estimation with Applications to Prediction and Classification
Jayadev Acharya,
Ashkan Jafarpour,
Alon Orlitsky,
Ananda Theertha Suresh
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PMLR 30:764-796
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Polynomial Time Optimal Query Algorithms for Finding Graphs with Arbitrary Real Weights
Sung-Soon Choi
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PMLR 30:797-818
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Differentially Private Feature Selection via Stability Arguments, and the Robustness of the Lasso
Abhradeep Guha Thakurta,
Adam Smith
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PMLR 30:819-850
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Learning a set of directions
Wouter M. Koolen,
Jiazhong Nie,
Manfred Warmuth
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PMLR 30:851-866
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A Tensor Spectral Approach to Learning Mixed Membership Community Models
Animashree Anandkumar,
Rong Ge,
Daniel Hsu,
Sham Kakade
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PMLR 30:867-881
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Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem
Ittai Abraham,
Omar Alonso,
Vasilis Kandylas,
Aleksandrs Slivkins
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PMLR 30:882-910
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Boosting with the Logistic Loss is Consistent
Matus Telgarsky
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PMLR 30:911-965
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Competing With Strategies
Wei Han,
Alexander Rakhlin,
Karthik Sridharan
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PMLR 30:966-992
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Online Learning with Predictable Sequences
Alexander Rakhlin,
Karthik Sridharan
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PMLR 30:993-1019
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Efficient Learning of Simplices
Joseph Anderson,
Navin Goyal,
Luis Rademacher
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PMLR 30:1020-1045
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Complexity Theoretic Lower Bounds for Sparse Principal Component Detection
Quentin Berthet,
Philippe Rigollet
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PMLR 30:1046-1066
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