Machine Learning, Volume 44, 2001

Volume 44, Number 1/2, July 2001

• Vasant Honavar, Colin de la Higuera:
  Introduction. 5-7
  
• Rajesh Parekh, Vasant Honavar:
  Learning DFA from Simple Examples. 9-35
  
• François Denis:
  Learning Regular Languages from Simple Positive Examples. 37-66
  
• Peter Rossmanith, Thomas Zeugmann:
  Stochastic Finite Learning of the Pattern Languages. 67-91
  
• Arlindo L. Oliveira, João P. Marques Silva:
  Efficient Algorithms for the Inference of Minimum Size DFAs. 93-119
  
• David Picó, Francisco Casacuberta:
  Some Statistical-Estimation Methods for Stochastic Finite-State Transducers. 121-141
  
• Juan-Carlos Amengual, Alberto Sanchís, Enrique Vidal, José-Miguel Benedí:
  Language Simplification through Error-Correcting and Grammatical Inference Techniques. 143-159
  
• C. Lee Giles, Steve Lawrence, Ah Chung Tsoi:
  Noisy Time Series Prediction using Recurrent Neural Networks and Grammatical Inference. 161-183
  
• Rafael C. Carrasco, José Oncina, Jorge Calera-Rubio:
  Stochastic Inference of Regular Tree Languages. 185-197
  

Volume 44, Number 3, September 2001

• Peter A. Flach, Saso Dzeroski:
  Editorial: Inductive Logic Programming is Coming of Age. 207-209
  
• Thomas R. Amoth, Paul Cull, Prasad Tadepalli:
  On Exact Learning of Unordered Tree Patterns. 211-243
  
• James Cussens:
  Parameter Estimation in Stochastic Logic Programs. 245-271
  
• Boonserm Kijsirikul, Sukree Sinthupinyo, Kongsak Chongkasemwongse:
  Approximate Match of Rules Using Backpropagation Neural Networks. 273-299
  
• Ashwin Srinivasan:
  Extracting Context-Sensitive Models in Inductive Logic Programming. 301-324
  

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