23. COLT 2010:
Haifa,
Israel
Adam Tauman Kalai, Mehryar Mohri (Eds.):
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 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 Imre 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
Last update Thu May 24 04:15:09 2012
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