16. ALT 2005: Singapore

• Sanjay Jain, Hans-Ulrich Simon, Etsuji Tomita:
  Editors' Introduction. 1-9
  

Invited Papers

• Gary Bradshaw:
  Invention and Artificial Intelligence. 10
  
• Neil R. Smalheiser:
  The Arrowsmith Project: 2005 Status Report. 11
  
• Ross D. King:
  The Robot Scientist Project. 12
  
• Doina Caragea, Jun Zhang, Jie Bao, Jyotishman Pathak, Vasant Honavar:
  Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. 13-44
  
• Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin:
  Training Support Vector Machines via SMO-Type Decomposition Methods. 45-62
  

Kernel-Based Learning

• Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf:
  Measuring Statistical Dependence with Hilbert-Schmidt Norms. 63-77
  
• Adam Kowalczyk, Olivier Chapelle:
  An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron. 78-91
  

Bayesian and Statistical Models

• Yang Bo He, Zhi Geng, Xun Liang:
  Learning Causal Structures Based on Markov Equivalence Class. 92-106
  
• Kazuho Watanabe, Sumio Watanabe:
  Stochastic Complexity for Mixture of Exponential Families in Variational Bayes. 107-121
  
• Risivardhan Thonangi, Vikram Pudi:
  ACME: An Associative Classifier Based on Maximum Entropy Principle. 122-134
  

PAC-Learning

• Jittat Fakcharoenphol, Boonserm Kijsirikul:
  Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors. 135-147
  
• Daniil Ryabko:
  On Computability of Pattern Recognition Problems. 148-156
  
• Nick Palmer, Paul W. Goldberg:
  PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance. 157-170
  
• Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson:
  Learnability of Probabilistic Automata via Oracles. 171-182
  

Query-Learning

• Rotem Bennet, Nader H. Bshouty:
  Learning Attribute-Efficiently with Corrupt Oracles. 183-197
  
• Wolfgang Lindner:
  Learning DNF by Statistical and Proper Distance Queries Under the Uniform Distribution. 198-210
  
• Hirotaka Kato, Satoshi Matsumoto, Tetsuhiro Miyahara:
  Learning of Elementary Formal Systems with Two Clauses Using Queries. 211-225
  
• Sanjay Jain, Steffen Lange, Sandra Zilles:
  Gold-Style and Query Learning Under Various Constraints on the Target Class. 226-240
  

Inductive Inference

• Lorenzo Carlucci, John Case, Sanjay Jain, Frank Stephan:
  Non U-Shaped Vacillatory and Team Learning. 241-255
  
• Sanjay Jain, Efim B. Kinber:
  Learning Multiple Languages in Groups. 256-268
  

Language Learning

• Yen Kaow Ng, Takeshi Shinohara:
  Inferring Unions of the Pattern Languages by the Most Fitting Covers. 269-282
  
• Alexander Clark, Rémi Eyraud:
  Identification in the Limit of Substitutable Context-Free Languages. 283-296
  
• Henning Fernau:
  Algorithms for Learning Regular Expressions. 297-311
  

Learning and Logic

• M. R. K. Krishna Rao:
  A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data. 312-326
  
• Sanjay Jain, Eric Martin, Frank Stephan:
  Absolute Versus Probabilistic Classification in a Logical Setting. 327-342
  

Learning from Expert Advice

• Shigeaki Harada, Eiji Takimoto, Akira Maruoka:
  Online Allocation with Risk Information. 343-355
  
• Jan Poland, Marcus Hutter:
  Defensive Universal Learning with Experts. 356-370
  
• Jussi Kujala, Tapio Elomaa:
  On Following the Perturbed Leader in the Bandit Setting. 371-385
  
• Matthew Henderson, John Shawe-Taylor, Janez Zerovnik:
  Mixture of Vector Experts. 386-398
  

Online Learning

• Chris Mesterharm:
  On-line Learning with Delayed Label Feedback. 399-413
  
• Alexey V. Chernov, Marcus Hutter:
  Monotone Conditional Complexity Bounds on Future Prediction Errors. 414-428
  

Defensive Forecasting

• Vladimir Vovk:
  Non-asymptotic Calibration and Resolution. 429-443
  
• Vladimir Vovk:
  Defensive Prediction with Expert Advice. 444-458
  
• Vladimir Vovk, Ilia Nouretdinov, Akimichi Takemura, Glenn Shafer:
  Defensive Forecasting for Linear Protocols. 459-473
  

Teaching

• Frank J. Balbach, Thomas Zeugmann:
  Teaching Learners with Restricted Mind Changes. 474-489