Learning context-free grammars with a simplicity bias

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1810, Issue , 2000, Pages 220-228

  Langley, Pat ^a   Stromsten, Sean ^a  

^a DaimlerChrysler Research and Technology North America Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MACHINE LEARNING;

BEAM SEARCH; LEARNING CONTEXT; NON-TERMINAL SYMBOLS; RATIONAL RECONSTRUCTION;

CONTEXT FREE GRAMMARS;

EID: 84974710157     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45164-1_23     Document Type: Conference Paper

References (5)

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2. Grünwald, P. (1996). A minimum description length approach to grammar inference. In S. Wermter, E. Riloff, & G. Scheler (Eds.) Connectionist, statistical and symbolic approaches to learning for natural language processing. Lecture Notes in Computer Science, 1040. Berlin: Springer-Verlag.
3. Stolcke, A. (1994). Bayesian learning of probabilistic language models. Doctoral dissertation, Division of Computer Science, University of California, Berkeley.
4. VanLehn, K., & Ball, W. (1987). A version space approach to learning context-free grammars. Machine Learning, 2, 39-74.
5. Wolff, J. G. (1982). Language acquisition, data compression and generalization. Language & Communication, 2, 57-89.