23. COLT 2010: Haifa, Israel

• 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 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page