17. ALT 2006: Barcelona, Spain

• José L. Balcázar, Philip M. Long, Frank Stephan:
  Editors' Introduction. 1-9
  

Invited Contributions

• Gunnar Rätsch:
  Solving Semi-infinite Linear Programs Using Boosting-Like Methods. 10-11
  
• Carole A. Goble, Óscar Corcho, Pinar Alper, David De Roure:
  e-Science and the Semantic Web: A Symbiotic Relationship. 12
  
• Hans-Ulrich Simon:
  Spectral Norm in Learning Theory: Some Selected Topics. 13-27
  
• Padhraic Smyth:
  Data-Driven Discovery Using Probabilistic Hidden Variable Models. 28
  
• Andrew Y. Ng:
  Reinforcement Learning and Apprenticeship Learning for Robotic Control. 29-31
  

Regular Contributions

• Alp Atici, Rocco A. Servedio:
  Learning Unions of omega(1)-Dimensional Rectangles. 32-47
  
• Nader H. Bshouty, Ehab Wattad:
  On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle. 48-62
  
• Matti Kääriäinen:
  Active Learning in the Non-realizable Case. 63-77
  
• Jorge Castro:
  How Many Query Superpositions Are Needed to Learn? 78-92
  
• Frank J. Balbach, Thomas Zeugmann:
  Teaching Memoryless Randomized Learners Without Feedback. 93-108
  
• Stephen A. Fenner, William I. Gasarch:
  The Complexity of Learning SUBSEQ (A). 109-123
  
• Matthew de Brecht, Akihiro Yamamoto:
  Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data. 124-138
  
• Sanjay Jain, Efim B. Kinber:
  Learning and Extending Sublanguages. 139-153
  
• Sanjay Jain, Efim B. Kinber:
  Iterative Learning from Positive Data and Negative Counterexamples. 154-168
  
• Sanjay Jain, Steffen Lange, Sandra Zilles:
  Towards a Better Understanding of Incremental Learning. 169-183
  
• Nader H. Bshouty, Iddo Bentov:
  On Exact Learning from Random Walk. 184-198
  
• Eyal Even-Dar, Michael J. Kearns, Jennifer Wortman:
  Risk-Sensitive Online Learning. 199-213
  
• Vladimir Vovk:
  Leading Strategies in Competitive On-Line Prediction. 214-228
  
• Chamy Allenberg, Peter Auer, László Györfi, György Ottucsák:
  Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring. 229-243
  
• Marcus Hutter:
  General Discounting Versus Average Reward. 244-258
  
• Jan Poland:
  The Missing Consistency Theorem for Bayesian Learning: Stochastic Model Selection. 259-273
  
• Shane Legg:
  Is There an Elegant Universal Theory of Prediction? 274-287
  
• Leonid Kontorovich, Corinna Cortes, Mehryar Mohri:
  Learning Linearly Separable Languages. 288-303
  
• Kohei Hatano:
  Smooth Boosting Using an Information-Based Criterion. 304-318
  
• Hsuan-Tien Lin, Ling Li:
  Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice. 319-333
  
• Daniil Ryabko, Marcus Hutter:
  Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. 334-347
  
• Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama:
  Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning. 348-362
  
• Andreas Maurer:
  Unsupervised Slow Subspace-Learning from Stationary Processes. 363-377
  
• Atsuyoshi Nakamura:
  Learning-Related Complexity of Linear Ranking Functions. 378-392