The 21st International Conference
Algorithmic Learning Theory

Canberra, Australia
October 6 - 8, 2010


     The following papers have been accepted for ALT 2010.
     There is no particular order in the list.

     Please keep in mind that we need your final version until

July 05, 2010.
     Please prepare your final version in accordance with the 
     Instructions for authors.

An Algorithm for Iterative Selection of Blocks of Feature Pierre Alquier

Toward a Classification of Finite Partial-Monitoring Games Gábor Bartók, Dávid Pál, and Csaba Szepesvári

Bayesian Active Learning Using Arbitrary Binary Valued Queries Liu Yang, Steve Hanneke, and Jaime Carbonell

PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation Balázs Csáji, Raphaël Jungers, and Vincent Blondel

Inductive Inference of Languages from Samplings Sanjay Jain and Efim Kinber

Compressed Learning with Regular Concept Jiawei Lv, Jianwen Zhang, Fei Wang, Zheng Wang, and Changshui Zhang

Optimality Issues of Universal Greedy Agents with Static Priors Laurent Orseau

Learning without Coding Samuel E. Moelius III and Sandra Zilles

Consistency of Feature Markov Processes Peter Sunehag and Marcus Hutter

Solutions to Open Questions for Non-U-Shaped Learning
with Memory Limitations
Timo Koetzing and John Case

Learning Figures with the Hausdorff Metric by Fractals Mahito Sugiyama, Eiju Hirowatari, Hideki Tsuiki, and Akihiro Yamamoto

Lower Bounds on Learning Random Structures with
Statistical Queries
Dana Angluin, David Eisenstat, Aryeh Kontorovich, and Lev Reyzin

A Lower Bound for Learning Distributions Generated by Probabilistic Automata Borja Balle, Jorge Castro, and Ricard Gavaldà

Inferring Social Networks from Outbreaks Dana Angluin, James Aspnes, and Lev Reyzin

A PAC-Bayes Bound for Tailored Density Estimation Matthew Higgs and John Shawe-Taylor

Recursive Teaching Dimension, Learning Complexity, and Maximum Classes Thorsten Doliwa, Hans Ulrich Simon, and Sandra Zilles

Distribution-Dependent PAC-Bayes Priors Guy Lever, François Laviolette and John Shawe-Taylor

Prediction with Expert Advice under Discounted Loss Alexey Chernov and Fedor Zhdanov

Online Multiple Kernel Learning: Algorithms and Mistake Bounds Rong Jin, Steven Hoi and Tianbao Yang

A Spectral Approach for Probabilistic Grammatical Inference on Trees Raphaël Bailly, François Denis, and Amaury Habrard

Switching Investments Wouter M. Koolen and Steven de Rooij.

An Identity for Kernel Ridge Regression Fedor Zhdanov and Yuri Kalnishkan

PAC learnability of a concept class under non-atomic measures: a problem by Vidyasagar Vladimir Pestov

Approximation Stability and Boosting Wei Gao and Zhi-Hua Zhou

A Regularization Approach to Metrical Task Systems Jacob Abernethy, Peter Bartlett, Niv Buchbinder, and Isabelle Stanton

Algorithms for Adversarial Bandit Problems with Multiple Plays Taishi Uchiya, Atsuyoshi Nakamura, and Mineichi Kudo

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