6. ALT 1995: Fukuoka, Japan

@proceedings{DBLP:conf/alt/1995,
  editor    = {Klaus P. Jantke and
               Takeshi Shinohara and
               Thomas Zeugmann},
  title     = {Algorithmic Learning Theory, 6th International Conference, ALT
               '95, Fukuoka, Japan, October 18-20, 1995, Proceedings},
  booktitle = {ALT},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {997},
  year      = {1995},
  isbn      = {3-540-60454-5},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

• Klaus P. Jantke, Takeshi Shinohara, Thomas Zeugmann: Editor's Introduction. ix-xv

Session 1

• Yasubumi Sakakibara:
  Grammatical Inference: An Old and New Paradigm. 1-24
  

Session 2

• Amr F. Fahmy, Robert S. Roos:
  Efficient Learning of Real Time One-Counter Automata. 25-40
  
• Takeshi Koshiba, Erkki Mäkinen, Yuji Takada:
  Learning Strongly Deterministic Even Linear Languages from Positive Examples. 41-54
  
• Hiroshi Sakamoto:
  Language Learning from Membership Queries and Characteristic Examples. 55-65
  
• Hiroki Arimura, Hiroki Ishizaka, Takeshi Shinohara:
  Learning Unions of Tree Patterns Using Queries. 66-79
  

Session 3

• Luc De Raedt, Wim Van Laer:
  Inductive Constraint Logic. 80-94
  
• M. R. K. Krishna Rao:
  Incremental Learning of Logic Programs. 95-109
  
• Akira Miyashiro, Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka:
  Learning Orthogonal F-Horn Formulas. 110-122
  

Session 4

• Peter Auer:
  Learning Nested Differences in the Presence of Malicious Noise. 123-137
  
• Atsuyoshi Nakamura, Shinji Miura:
  Learning Sparse Linear Combinations of Basis Functions over a Finite Domain. 138-150
  

Session 5

• John D. Kececioglu, Ming Li, John Tromp:
  Inferring a DNA Sequence from Erroneous Copies (Abstract). 151-152
  

Session 6

• John Case, Sanjay Jain, Arun Sharma:
  Machine Induction Without Revolutionary Paradigm Shifts. 153-168
  
• Léa Meyer:
  Probabilistic Language Learning Under Monotonicity Constraints. 169-184
  
• Frank Stephan:
  Noisy Inference and Oracles. 185-200
  
• Bala Kalyanasundaram, Mahendran Velauthapillai:
  Simulating Teams with Many Conjectures. 201-214
  

Session 7

• Charles C. Pinter:
  Complexity of Network Training for Classes of Neural Networks. 215-227
  
• Ricard Gavaldà, David Guijarro:
  Learning Ordered Binary Decision Diagrams. 228-238
  
• Jorge Castro, José L. Balcázar:
  Simple PAC Learning of Simple Decision Lists. 239-248
  

Session 8

• Carlos Domingo, John Shawe-Taylor:
  The Complexity of Learning Minor Closed Graph Classes. 249-260
  

Session 9

• Yves Kodratoff:
  Technical and Scientific Issues of KDD (or: Is KDD a Science?). 261-265
  

Session 10

• Ken Sadohara, Makoto Haraguchi:
  Analogical Logic Program Synthesis Algorithm That Can Refute Inappropriate Similarities. 266-281
  
• Klaus P. Jantke:
  Reflecting and Self-Confident Inductive Inference Machines. 282-297
  
• Satoshi Kobayashi, Takashi Yokomori:
  On Approximately Identifying Concept Classes in the Limit. 298-312
  
• Andris Ambainis:
  Application of Kolmogorov Complexity to Inductive Inference with Limited Memory. 313-318
  

Last update Tue May 22 22:01:32 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page