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UAI
1998
15 years 4 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
AAAI
1992
15 years 4 months ago
Learning to Disambiguate Relative Pronouns
In this paper we show how a natural language system can learn to find the antecedents of relative pronouns. We use a well-known conceptual clustering system to create a case-based...
Claire Cardie
JUCS
2008
139views more  JUCS 2008»
15 years 3 months ago
A Progressive Learning Method for Symbol Recognition
: This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propos...
Sabine Barrat, Salvatore Tabbone
DEBU
2000
95views more  DEBU 2000»
15 years 3 months ago
Accurately and Reliably Extracting Data from the Web: A Machine Learning Approach
A critical problem in developing information agents for the Web is accessing data that is formatted for human use. We have developed a set of tools for extracting data from web si...
Craig A. Knoblock, Kristina Lerman, Steven Minton,...
AI
1999
Springer
15 years 3 months ago
Learning Action Strategies for Planning Domains
There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. ...
Roni Khardon