The 16th International Conference
Algorithmic Learning Theory

Marina Mandarin Hotel, Singapore, Republic of Singapore
October 8 - 11, 2005


     The following papers have been accepted for ALT 2005.
     There is no particular order in the list.

     Please keep in mind that we need your final version until

                July 20, 2005. 

Non-asymptotic Calibration and Resolution Vladimir Vovk

Learning Multiple Languages in Groups

Sanjay Jain and Efim Kinber
PAC-learnability of Probabilistic Deterministic Finite State Automata in terms of Variation Distance

Nick Palmer and Paul Goldberg
Measuring Statistical Dependence with Hilbert-Schmidt Norms

Arthur Gretton, Olivier Bousquet, Alex Smola, and Bernhard Schölkopf
Learning Attribute-Efficiently with Corrupt Oracles

Nader Bshouty and Rotem Bennet
Decision-theoretic Aspects of Defensive Forecasting Vladimir Vovk

Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors

Jittat Fakcharoenphol and Boonserm Kijsirikul
Inferring Unions of the Pattern Languages by The Most Fitting Covers

Yen Kaow Ng and Takeshi Shinohara
Gold-style and Query Learning under Various Constraints on the Target Class Sanjay Jain, Steffen Lange, and Sandra Zilles

On Computability of Pattern Recognition Problems

Daniil Ryabko
Defensive Forecasting for Linear Protocols

Vladimir Vovk, Ilia Nouretdinov, Akimichi Takemura, and Glenn Shafer
Identification in the Limit of Substitutable Context Free Languages Alexander Clark and Remi Eyraud

Stochastic Complexity for Mixture of Exponential Families in Variational Bayes

Kazuho Watanabe and Sumio Watanabe
Non U-Shaped Vacillatory and Team Learning Lorenzo Carlucci, John Case, Sanjay Jain, and Frank Stephan

Algorithms for Learning Regular Expressions

Henning Fernau
Monotone Conditional Complexity Bounds on Future Prediction Errors Alexey Chernov and Marcus Hutter

Teaching Learners With Restricted Mind Changes

Frank J. Balbach and Thomas Zeugmann
Learning DNF by Statistical and Proper Distance Queries under the Uniform Distribution

Wolfgang Lindner
Learning of Elementary Formal Systems with Two Clauses using Queries

Hirotaka Kato, Satoshi Matsumoto, and Tetsuhiro Miyahara
On Following the Perturbed Leader in the Bandit Setting

Jussi Kujala and Tapio Elomaa
Learnability of Probabilistic Automata via Oracles

Omri Guttman, S.V.N. Vishwanathan, Robert C. Williamson
Online Allocation with Risk Information

Shigeaki Harada, Eiji Takimoto, and Akira Maruoka
A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data

M. R. K. Krishna Rao

Absolute versus Probabilistic Classification in a Logical Setting

Sanjay Jain, Eric Martin, and Frank Stephan
Learning Causal Structures Based on Markov Equivalence Classes

Yangbo He, Zhi Geng, and Xun Liang
An Analysis of the Anti-Learning Phenomenon for the Class Symmetric Polyhedron

Adam Kowalczyk and Olivier Chapelle
An Associative Classifier based on Maximum Entropy Principle

Risi Thonangi and Vikram Pudi
Defensive Universal Learning with Experts

Jan Poland and Marcus Hutter
Consistency and Generalization Bounds for Maximum Entropy Density Estimation

Shaojun Wang, Russell Greiner, Dale Schuurmans. and Shaomin Wang
On-line Learning with Delayed Label Feedback

Chris Mesterharm
Mixture of Vector Experts

Matthew Henderson, John Shawe-Taylor, and Janez Zerovnik

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