Abstract is missing.
- Editors IntroductionJosé L. Balcázar, Philip M. Long, Frank Stephan. 1-9 [doi]
- Solving Semi-infinite Linear Programs Using Boosting-Like MethodsGunnar Rätsch. 10-11 [doi]
- e-Science and the Semantic Web: A Symbiotic RelationshipCarole A. Goble, Óscar Corcho, Pinar Alper, David De Roure. 12 [doi]
- Spectral Norm in Learning Theory: Some Selected TopicsHans-Ulrich Simon. 13-27 [doi]
- Data-Driven Discovery Using Probabilistic Hidden Variable ModelsPadhraic Smyth. 28 [doi]
- Reinforcement Learning and Apprenticeship Learning for Robotic ControlAndrew Y. Ng. 29-31 [doi]
- Learning Unions of ::::omega::::(1)-Dimensional RectanglesAlp Atici, Rocco A. Servedio. 32-47 [doi]
- On Exact Learning Halfspaces with Random Consistent Hypothesis OracleNader H. Bshouty, Ehab Wattad. 48-62 [doi]
- Active Learning in the Non-realizable CaseMatti Kääriäinen. 63-77 [doi]
- How Many Query Superpositions Are Needed to Learn?Jorge Castro. 78-92 [doi]
- Teaching Memoryless Randomized Learners Without FeedbackFrank J. Balbach, Thomas Zeugmann. 93-108 [doi]
- The Complexity of Learning SUBSEQ (::::A::::)Stephen A. Fenner, William I. Gasarch. 109-123 [doi]
- Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive DataMatthew de Brecht, Akihiro Yamamoto. 124-138 [doi]
- Learning and Extending SublanguagesSanjay Jain, Efim B. Kinber. 139-153 [doi]
- Iterative Learning from Positive Data and Negative CounterexamplesSanjay Jain, Efim B. Kinber. 154-168 [doi]
- Towards a Better Understanding of Incremental LearningSanjay Jain, Steffen Lange, Sandra Zilles. 169-183 [doi]
- On Exact Learning from Random WalkNader H. Bshouty, Iddo Bentov. 184-198 [doi]
- Risk-Sensitive Online LearningEyal Even-Dar, Michael J. Kearns, Jennifer Wortman. 199-213 [doi]
- Leading Strategies in Competitive On-Line PredictionVladimir Vovk. 214-228 [doi]
- Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial MonitoringChamy Allenberg, Peter Auer, László Györfi, György Ottucsák. 229-243 [doi]
- General Discounting Versus Average RewardMarcus Hutter. 244-258 [doi]
- The Missing Consistency Theorem for Bayesian Learning: Stochastic Model SelectionJan Poland. 259-273 [doi]
- Is There an Elegant Universal Theory of Prediction?Shane Legg. 274-287 [doi]
- Learning Linearly Separable LanguagesLeonid Kontorovich, Corinna Cortes, Mehryar Mohri. 288-303 [doi]
- Smooth Boosting Using an Information-Based CriterionKohei Hatano. 304-318 [doi]
- Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and PracticeHsuan-Tien Lin, Ling Li. 319-333 [doi]
- Asymptotic Learnability of Reinforcement Problems with Arbitrary DependenceDaniil Ryabko, Marcus Hutter. 334-347 [doi]
- Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement LearningTakeshi Shibata, Ryo Yoshinaka, Takashi Chikayama. 348-362 [doi]
- Unsupervised Slow Subspace-Learning from Stationary ProcessesAndreas Maurer. 363-377 [doi]
- Learning-Related Complexity of Linear Ranking FunctionsAtsuyoshi Nakamura. 378-392 [doi]