COLT 2010 - Program


Friday June 25	ICML/COLT Joint Workshop Day
Saturday June 26	ICML/COLT Tourist Trip

Sunday June 27	COLT Conference
08:35 - 08:45	Opening Remarks
08:45 - 09:35	Online Convex Optimization: Nicolò Cesa-Bianchi Convex Games in Banach Spaces Karthik Sridharan, Ambuj Tewari Efficient Classification for Metric Data Lee-Ad Gottlieb, Aryeh (Leonid) Kontorovich, Robi Krauthgamer [Presentation]
09:35 - 10:00	Coffee Break
10:00 - 11:00	Invited Talk (Noga Alon): Mehryar Mohri [Presentation]
11:05 - 12:45	Bandit Algorithms: Yishay Mansour Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback Alekh Agarwal, Ofer Dekel, Lin Xiao [Presentation] Best Arm Identification in Multi-Armed Bandits Jean-Yves Audibert, Sébastien Bubeck, Rémi Munos [Presentation] Nonparametric Bandits with Covariates Philippe Rigollet, Assaf Zeevi [Presentation] An Asymptotically Optimal Bandit Algorithm for Bounded Support Models Junya Honda, Akimichi Takemura [Presentation]
12:45 - 14:20	Lunch Break
14:20 - 16:00	Online Learning (I): Phil Long Learning with Global Cost in Stochastic Environments Eyal Even-Dar, Shie Mannor, Yishay Mansour [Presentation] Hedging Structured Concepts Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen [ Presentation] Following the Flattened Leader Wojciech Kotlowski, Peter Grunwald, Steven de Rooij [Presentation] Sequence prediction in realizable and non-realizable cases Daniil Ryabko
16:00 - 16:30	Coffee Break
16:30 - 18:10	Regret Minimization and Drifting: Sham Kakade Regret Minimization for Online Buffering Problems Using the Weighted Majority Algorithm Sascha Geulen, Berthold Voecking, Melanie Winkler [Presentation] Learning rotations with little regret Elad Hazan, Satyen Kale, Manfred Warmuth [Presentation] Evolution with Drifting Targets Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan [Presentation] Regret Minimization with Concept Drift Koby Crammer, Eyal Even-Dar, Yishay Mansour, Jennifer Wortman Vaughan
18:10 - 20:30	Dinner Break
20:30 - 22:00	Business Meeting (in pajamas)

Monday June 28	COLT Conference
08:45 - 10:00	Inductive inference and quantum learning: Adam Kalai Strongly Non-U-Shaped Learning Results by General Techniques Timo Kötzing, John Case [Presentation] Inferring Descriptive Generalisations of Formal Languages Dominik Freydenberger, Daniel Reidenbach [Presentation] Ranking with kernels in Fourier space Risi Kondor, Marconi Barbosa [Presentation]
10:00 - 10:20	Coffee Break
10:20 - 12:00	Online Learning (II): Katrina Ligett Online Learning of Noisy Data with Kernels Nicolo Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir [Presentation] The Online Loop-free Stochastic Shortest-Path Problem Andras Gyorgy, Gergely Neu, Csaba Szepesvari Adaptive Bound Optimization for Online Convex Optimization H. Brendan McMahan, Matthew Streeter Adaptive Subgradient Methods for Online Learning and Stochastic Optimization John Duchi, Elad Hazan, Yoram Singer [Presentation]
12:00 - 13:25	Lunch Break
13:25 - 14:40	Clustering and Link Prediction: Ulrike Von Luxburg Characterization of Linkage-based Clustering Margareta Ackerman, Shai Ben-David, David Loker [Presentation] Robust Hierarchical Clustering Maria-Florina Balcan, Pramod Gupta [Presentation] Theoretical Justification of Popular Link Prediction Heuristics Purnamrita Sarkar, Deepayan Chakrabarti, Andrew Moore
14:40 - 15:00	Coffee Break
15:00 - 16:00	Invited Talk (Noam Nisan): Adam Kalai [Presentation]
16:00 - 17:20	Open problem Session: Claudio Gentile The Convergence Rate of Adaboost Robert Schapire Learning Talagrand DNF formulas Homin Lee [Presentation] Challenge Problem: Analyzing Ant Robot Coverage Sven Koenig Online Variance Minimization in O(n^2) per Trial? Elad Hazan, Satyen Kale, Manfred Warmuth [Presentation] Robust Efficient Conditional Probability Estimation John Langford Can Learn to Gamble Efficiently? Jacob Abernethy, Eli Ben-Sasson, Hamid Nazer Zadeh
17:20 - 17:40	Break + Getting Ready for the Banquet
17:40	Depart for Nazareth Banquet

Tuesday June 29	COLT Conference
08:45 - 10:00	Active Learning: Ofer Dekel Active Learning on Trees and Graphs Nicolo' Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization Daniel Golovin, Andreas Krause [Presentation] Robust Selective Sampling from Single and Multiple Teachers Ofer Dekel, Claudio Gentile, Karthik Sridharan
10:00 - 10:20	Coffee Break
10:20 - 12:00	PAC Learning: Manfred Warmuth Improved Guarantees for Agnostic Learning of Disjunctions Pranjal Awasthi, Avrim Blum, Or Sheffet Mansour's Conjecture is True for Random DNF Formulas Adam Klivans, Homin Lee, Andrew Wan [Presentation] Deterministic Sparse Fourier Approximation via Fooling Arithmetic Progressions Adi Akavia Learning to create is as hard as learning to appreciate David Xiao
12:00 - 13:30	Lunch Break
13:30 - 15:10	Density Estimation and Other Directions (I): Shai Ben-David Forest Density Estimation Anupam Gupta, John Lafferty, Han Liu, Larry Wasserman, Min Xu Toward Learning Gaussian Mixtures with Arbitrary Separation Mikhail Belkin, Kaushik Sinha Sparse Recovery in Convex Hulls of Infinite Dictionaries Vladimir Koltchinskii, Stas Minsker Composite Objective Mirror Descent John Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari [Presentation]
15:10 - 15:40	Coffee Break
15:40 - 17:20	Other Directions (II): Mikhail Belkin Learning Kernel-Based Halfspaces with the Zero-One Loss Ohad Shamir, Shai Shalev-Shwartz, Karthik Sridharan [Presentation] Quantum Predictive Learning and Communication Complexity with Single Input Dmitry Gavinsky Causal Markov condition for submodular information measures Bastian Steudel, Dominik Janzing, Bernhard Schoelkopf Open Loop Optimistic Planning Sébastien Bubeck, Rémi Munos [Presentation]
17:20 - 17:40	Coffee Break
17:40 - 18:30	Robustness: Shai Shalev-Shwartz Principal Component Analysis with Contaminated Data: The High Dimensional Case Huan Xu, Constantine Caramanis, Shie Mannor [Presentation] Robustness and Generalization Huan Xu, Shie Mannor [Presentation]