Table of Contents

Editors' Introduction		1 - 9
José L. Balcázar, Philip M. Long, and Frank Stephan
INVITED CONTRIBUTIONS
Solving Semi-infinite Linear Programs Using Boosting-Like Methods, Abstract and Slides.		10 - 11
Gunnar Rätsch
e-Science and the Semantic Web: A Symbiotic Relationship, Abstract.		12
Carole Goble, Oscar Corcho and Pinar Alper and David De Roure
Spectral Norm in Learning Theory: Some Selected Topics, Abstract and Slides.		13 - 27
Hans Ulrich Simon,
Data-Driven Discovery Using Probabilistic Hidden Variable Models, Abstract.		28
Padhraic Smyth
Reinforcement Learning and Apprenticeship Learning for Robotic Control, Abstract.		29
Andrew Y. Ng
REGULAR CONTRIBUTIONS
Learning unions of ω(1)-dimensional rectangles, Abstract.		32 - 47
Alp Atıcı and Rocco Servedio
On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle, Abstract.		48 - 62
Nader H. Bshouty and Ehab Wattad
Active Learning in the Non-realizable Case, Abstract.		63 - 77
Matti Kääriäinen
How Many Query Superpositions Are Needed to Learn?, Abstract.		78 - 92
Jorge Castro
Teaching Memoryless Randomized Learners Without Feedback, Abstract.		93 - 108
Frank J. Balbach and Thomas Zeugmann
The Complexity of Learning SUBSEQ(A), Abstract.		109 - 123
Stephen Fenner and William Gasarch
Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data, Abstract.		124 - 138
Matthew de Brecht and Akihiro Yamamoto
Learning and Extending Sublanguages, Abstract.		139 - 153
Sanjay Jain and Efim Kinber
Iterative Learning from Positive Data and Negative Counterexamples, Abstract.		154 - 168
Sanjay Jain and Efim Kinber
Towards a Better Understanding of Incremental Learning, Abstract.		169 - 183
Sanjay Jain, Steffen Lange and Sandra Zilles
On Exact Learning from Random Walk, Abstract.		184 - 198
Nader H. Bshouty and Iddo Bentov
Risk-Sensitive Online Learning, Abstract.		199 - 213
Eyal Even-Dar, Michael Kearns and Jennifer Wortman
Leading Strategies in Competitive On-Line Prediction, Abstract.		214 - 228
Vladimir Vovk
Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring, Abstract.		229 - 243
Chamy Allenberg, Peter Auer, László Györfi, and György Ottucsák
General Discounting Versus Average Reward, Abstract.		244 - 258
Marcus Hutter
The Missing Consistency Theorem for Bayesian Learning: Stochastic Model Selection, Abstract.		259 - 273
Jan Poland
Is There an Elegant Universal Theory of Prediction?, Abstract.		274 - 287
Shane Legg
Learning Linearly Separable Languages, Abstract.		288 - 303
Leonid Kontorovich, Corinna Cortes and Mehryar Mohri Smooth Boosting Using an Information-Based Criterion, Abstract.		304 - 318
Kohei Hatano
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice, Abstract.		319 - 333
Hsuan-Tien Lin and Ling Li
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence, Abstract.		334 - 347
Daniil Ryabko and Marcus Hutter
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning, Abstract.		348 - 362
Takeshi Shibata, Ryo Yoshinaka and Takashi Chikayama
Unsupervised Slow Subspace-Learning from Stationary Processes, Abstract.		363 - 377
Andreas Maurer
Learning-Related Complexity of Linear Ranking Functions, Abstract.		378 - 392
Atsuyoshi Nakamura
Author Index		393

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