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ACL
1994
13 years 11 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
JMLR
2006
169views more  JMLR 2006»
13 years 10 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
ICRA
2008
IEEE
119views Robotics» more  ICRA 2008»
14 years 4 months ago
Towards schema-based, constructivist robot learning: Validating an evolutionary search algorithm for schema chunking
— In this paper, we lay the groundwork for extending our previously developed ASyMTRe architecture to enable constructivist learning for multi-robot team tasks. The ASyMTRe archi...
Yifan Tang, Lynne E. Parker
SIGCSE
2002
ACM
152views Education» more  SIGCSE 2002»
13 years 10 months ago
Learning styles and performance in the introductory programming sequence
This paper reports on the implication of different preferred learning styles on students'performance in the introductory programming sequence and on work in progress on how t...
Lynda Thomas, Mark Ratcliffe, John Woodbury, Emma ...
ML
2007
ACM
130views Machine Learning» more  ML 2007»
13 years 9 months ago
Interactive learning of node selecting tree transducer
We develop new algorithms for learning monadic node selection queries in unranked trees from annotated examples, and apply them to visually interactive Web information extraction. ...
Julien Carme, Rémi Gilleron, Aurélie...