The 19th International Conference
Algorithmic Learning Theory

Hotel Budapest, Budapest, Hungary
October 13 - 16, 2008


     The following papers have been accepted for ALT 2008.
     There is no particular order in the list.

     Please keep in mind that we need your final version until

July 20, 2008.
     Please prepare your final version in accordance with the 
     Instructions for authors.

Query Learning and Certificates in Lattices M. Arias and J.L. Balcázar

Optimally Learning Social Networks with Activations and Suppressions Dana Angluin, James Aspnes, and Lev Reyzin

Active Learning in Multi-Armed Bandits Andras Antos, Varun Grover, and Csaba Szepesvári

Generalization Bounds for Some Ordinal Regression Algorithms Shivani Agarwal

Aggregating Algorithm for a Space of Analytic Functions Mikhail Dashevskiy

Iterative Learning of Simple External Contextual Languages Leonor Becerra-Bonache, John Case, Sanjay Jain, and Frank Stephan

Active Learning of Group-Structured Environments Gábor Bartók, Csaba Szepesvári, and Sandra Zilles

Clustering with Interactive Feedback Maria-Florina Balcan and Avrim Blum

Dynamically Delayed Postdictive Completeness and Consistency in Learning John Case and Timo Koetzing

Dynamic Modeling in Inductive Inference John Case and Timo Koetzing

Supermartingales in Prediction with Expert Advice Alexey Chernov, Yuri Kalnishkan, Vladimir Vovk, and Fedor Zhdanov

On-line Probability, Complexity and Randomness Alexey Chernov, Alexander Shen, Nikolai Vereshchagin, and Vladimir Vovk

Approximation of the Optimal ROC Curve and a Tree-based Ranking Algorithm Stéphan Clémençon and Nicolas Vayatis

Sample Selection Bias Correction Theory Corinna Cortes, Mehryar Mohri, Michael Riley, and Afshin Rostamizadeh

Growth Optimal Investment with Transaction Costs László Györfi and István Vajda

Nonparametric Independence Tests: Space Partitioning and Kernel Approaches Arthur Gretton and László Györfi

Exploiting Cluster-Structure to Predict the Labeling of a Graph Mark Herbster

Finding the Rare Cube Shlomo Hoory and Oded Margalit

Numberings Optimal for Learning Sanjay Jain and Frank Stephan

Learning with Temporary Memory Steffen Lange, Samuel E. Moelius III, and Sandra Zilles

Uniform error bounds for K-dimensional coding schemes in Hilbert spaces Andreas Maurer and Massimiliano Pontil

Learning with Continuous Experts Using Drifting Games Indraneel Mukherjee and Robert E. Schapire

Prequential Randomness Vladimir Vovk and Alexander Shen

Learning and Generalization with the Information Bottleneck Ohad Shamir, Sivan Sabato, and Naftali Tishby

Online Regret Bounds for Markov Decision Processes with Deterministic Transitions Ronald Ortner

Some Sufficient Conditions on an Arbitrary Class of Stochastic Processes for the Existence of a Predictor Daniil Ryabko

Entropy Regularized LPBoost Manfred K. Warmuth, Karen A. Glocer, and S.V.N. Vishwanathan

Optimal Language Learning John Case and Samuel E. Moelius III

Smooth Boosting for Margin-Based Ranking Jun-ichi Moribe, Kohei Hatano, Eiji Takimoto, and Masayuki Takeda

Topological Properties of Concept Spaces Matthew de Brecht and Akihiro Yamamoto

A Uniform Lower Error Bound for Half-space Learning Andreas Maurer and Massimiliano Pontil

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