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23rd COLT 2010: Haifa, Israel
- Adam Tauman Kalai, Mehryar Mohri:
COLT 2010 - The 23rd Conference on Learning Theory, Haifa, Israel, June 27-29, 2010. Omnipress 2010, ISBN 978-0-9822529-2-5 - Karthik Sridharan, Ambuj Tewari:
Convex Games in Banach Spaces. 1-13 - John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari:
Composite Objective Mirror Descent. 14-26 - Noga Alon:
Voting Paradoxes. 27 - Alekh Agarwal, Ofer Dekel, Lin Xiao:
Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback. 28-40 - Jean-Yves Audibert, Sébastien Bubeck, Rémi Munos:
Best Arm Identification in Multi-Armed Bandits. 41-53 - Philippe Rigollet, Assaf Zeevi:
Nonparametric Bandits with Covariates. 54-66 - Junya Honda, Akimichi Takemura:
An Asymptotically Optimal Bandit Algorithm for Bounded Support Models. 67-79 - Eyal Even-Dar, Shie Mannor, Yishay Mansour:
Learning with Global Cost in Stochastic Environments. 80-92 - Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen:
Hedging Structured Concepts. 93-105 - Wojciech Kotlowski, Peter Grünwald, Steven de Rooij:
Following the Flattened Leader. 106-118 - Daniil Ryabko:
Sequence Prediction in Realizable and Non-realizable Cases. 119-131 - Sascha Geulen, Berthold Vöcking, Melanie Winkler:
Regret Minimization for Online Buffering Problems Using the Weighted Majority Algorithm. 132-143 - Elad Hazan, Satyen Kale, Manfred K. Warmuth:
Learning Rotations with Little Regret. 144-154 - Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan:
Evolution with Drifting Targets. 155-167 - Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jennifer Wortman Vaughan:
Regret Minimization With Concept Drift. 168-180 - John Case, Timo Kötzing:
Strongly Non-U-Shaped Learning Results by General Techniques. 181-193 - Dominik D. Freydenberger, Daniel Reidenbach:
Inferring Descriptive Generalisations of Formal Languages. 194-206 - Dmitry Gavinsky:
Quantum Predictive Learning and Communication Complexity with Single Input. 207-217 - Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir:
Online Learning of Noisy Data with Kernels. 218-230 - Gergely Neu, András György, Csaba Szepesvári:
The Online Loop-free Stochastic Shortest-Path Problem. 231-243 - H. Brendan McMahan, Matthew J. Streeter:
Adaptive Bound Optimization for Online Convex Optimization. 244-256 - John C. Duchi, Elad Hazan, Yoram Singer:
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. 257-269 - Margareta Ackerman, Shai Ben-David, David Loker:
Characterization of Linkage-based Clustering. 270-281 - Maria-Florina Balcan, Pramod Gupta:
Robust Hierarchical Clustering. 282-294 - Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore:
Theoretical Justification of Popular Link Prediction Heuristics. 295-307 - Robert E. Schapire:
The Convergence Rate of AdaBoost. 308-309 - Homin K. Lee:
Learning Talagrand DNF Formulas. 310-311 - Sven Koenig:
Open Problem: Analyzing Ant Robot Coverage. 312-313 - Elad Hazan, Satyen Kale, Manfred K. Warmuth:
On-line Variance Minimization in O(n2) per Trial? 314-315 - John Langford:
Robust Efficient Conditional Probability Estimation. 316-317 - Jacob D. Abernethy:
Can We Learn to Gamble Efficiently? 318-319 - Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella:
Active Learning on Trees and Graphs. 320-332 - Daniel Golovin, Andreas Krause:
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization. 333-345 - Ofer Dekel, Claudio Gentile, Karthik Sridharan:
Robust Selective Sampling from Single and Multiple Teachers. 346-358 - Pranjal Awasthi, Avrim Blum, Or Sheffet:
Improved Guarantees for Agnostic Learning of Disjunctions. 359-367 - Adam R. Klivans, Homin K. Lee, Andrew Wan:
Mansour's Conjecture is True for Random DNF Formulas. 368-380 - Adi Akavia:
Deterministic Sparse Fourier Approximation via Fooling Arithmetic Progressions. 381-393 - Anupam Gupta, John D. Lafferty, Han Liu, Larry A. Wasserman, Min Xu:
Forest Density Estimation. 394-406 - Mikhail Belkin, Kaushik Sinha:
Toward Learning Gaussian Mixtures with Arbitrary Separation. 407-419 - Vladimir Koltchinskii, Stas Minsker:
Sparse Recovery in Convex Hulls of Infinite Dictionaries. 420-432 - Lee-Ad Gottlieb, Leonid Kontorovich, Robert Krauthgamer:
Efficient Classification for Metric Data. 433-440 - Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan:
Learning Kernel-Based Halfspaces with the Zero-One Loss. 441-450 - Risi Kondor, Marconi S. Barbosa:
Ranking with Kernels in Fourier space. 451-463 - Bastian Steudel, Dominik Janzing, Bernhard Schölkopf:
Causal Markov Condition for Submodular Information Measures. 464-476 - Sébastien Bubeck, Rémi Munos:
Open Loop Optimistic Planning. 477-489 - Huan Xu, Constantine Caramanis, Shie Mannor:
Principal Component Analysis with Contaminated Data: The High Dimensional Case. 490-502 - Huan Xu, Shie Mannor:
Robustness and Generalization. 503-515 - David Xiao:
Learning to Create is as Hard as Learning to Appreciate. 516-528
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