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AMAI
2004
Springer
15 years 9 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
ISER
2004
Springer
143views Robotics» more  ISER 2004»
15 years 9 months ago
Imitation Learning Based on Visuo-Somatic Mapping
Abstract. Imitation learning is a powerful approach to humanoid behavior generation, however, the most existing methods assume the availability of the information on the internal s...
Minoru Asada, Masaki Ogino, Shigeo Matsuyama, Jun'...
127
Voted
EUROCOLT
1999
Springer
15 years 8 months ago
Mind Change Complexity of Learning Logic Programs
The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds ...
Sanjay Jain, Arun Sharma
158
Voted
NIPS
1990
15 years 5 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
INFORMATICALT
2006
88views more  INFORMATICALT 2006»
15 years 4 months ago
Improving the Performances of Asynchronous Algorithms by Combining the Nogood Processors with the Nogood Learning Techniques
Abstract. The asynchronous techniques that exist within the programming with distributed constraints are characterized by the occurrence of the nogood values during the search for ...
Ionel Muscalagiu, Vladimir Cretu