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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

09:35 - 10:00

Coffee Break

10:00 - 11:00

Invited Talk (Noga Alon): Mehryar Mohri

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

Best Arm Identification in Multi-Armed Bandits
Jean-Yves Audibert, Sébastien Bubeck, Rémi Munos

Nonparametric Bandits with Covariates
Philippe Rigollet, Assaf Zeevi

An Asymptotically Optimal Bandit Algorithm for Bounded Support Models
Junya Honda, Akimichi Takemura

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

Hedging Structured Concepts
Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen
[ Presentation]

Following the Flattened Leader
Wojciech Kotlowski, Peter Grunwald, Steven de Rooij

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

Learning rotations with little regret
Elad Hazan, Satyen Kale, Manfred Warmuth

Evolution with Drifting Targets
Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan

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

Inferring Descriptive Generalisations of Formal Languages
Dominik Freydenberger, Daniel Reidenbach

Ranking with kernels in Fourier space
Risi Kondor, Marconi Barbosa

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

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

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

Robust Hierarchical Clustering
Maria-Florina Balcan, Pramod Gupta

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

16:00 - 17:20

Open problem Session: Claudio Gentile

The Convergence Rate of Adaboost
Robert Schapire

Learning Talagrand DNF formulas
Homin Lee

Challenge Problem: Analyzing Ant Robot Coverage
Sven Koenig

Online Variance Minimization in O(n^2) per Trial?
Elad Hazan, Satyen Kale, Manfred Warmuth

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


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

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

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

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

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

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

Robustness and Generalization
Huan Xu, Shie Mannor