ALT 2006

29 papers

Active Learning in the Non-Realizable Case Matti Kääriäinen

Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence Daniil Ryabko, Marcus Hutter

Data-Driven Discovery Using Probabilistic Hidden Variable Models Padhraic Smyth

E-Science and the Semantic Web: A Symbiotic Relationship Carole A. Goble, Óscar Corcho, Pinar Alper, David De Roure

General Discounting Versus Average Reward Marcus Hutter

Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring Chamy Allenberg, Peter Auer, László Györfi, György Ottucsák

How Many Query Superpositions Are Needed to Learn? Jorge Castro

Is There an Elegant Universal Theory of Prediction? Shane Legg

Iterative Learning from Positive Data and Negative Counterexamples Sanjay Jain, Efim B. Kinber

Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice Hsuan-Tien Lin, Ling Li

Leading Strategies in Competitive On-Line Prediction Vladimir Vovk

Learning and Extending Sublanguages Sanjay Jain, Efim B. Kinber

Learning Linearly Separable Languages Leonid Kontorovich, Corinna Cortes, Mehryar Mohri

Learning Unions of Omega(1)-Dimensional Rectangles Alp Atici, Rocco A. Servedio

Learning-Related Complexity of Linear Ranking Functions Atsuyoshi Nakamura

Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data Matthew de Brecht, Akihiro Yamamoto

On Exact Learning from Random Walk Nader H. Bshouty, Iddo Bentov

On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle Nader H. Bshouty, Ehab Wattad

Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama

Reinforcement Learning and Apprenticeship Learning for Robotic Control Andrew Y. Ng

Risk-Sensitive Online Learning Eyal Even-Dar, Michael J. Kearns, Jennifer Wortman

Smooth Boosting Using an Information-Based Criterion Kohei Hatano

Solving Semi-Infinite Linear Programs Using Boosting-like Methods Gunnar Rätsch

Spectral Norm in Learning Theory: Some Selected Topics Hans Ulrich Simon

Teaching Memoryless Randomized Learners Without Feedback Frank J. Balbach, Thomas Zeugmann

The Complexity of Learning SUBSEQ (a) Stephen A. Fenner, William I. Gasarch

The Missing Consistency Theorem for Bayesian Learning: Stochastic Model Selection Jan Poland

Towards a Better Understanding of Incremental Learning Sanjay Jain, Steffen Lange, Sandra Zilles

Unsupervised Slow Subspace-Learning from Stationary Processes Andreas Maurer