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COLT
1994
Springer
13 years 11 months ago
1994
Springer
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
JMLR
2006
13 years 7 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
IJAR
2007
13 years 7 months ago
2007
Pseudo-independent (PI) models are a special class of probabilistic domain model (PDM) where a set of marginally independent domain variables shows collective dependency, a specia...
ICPR
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
ACL
2001
13 years 8 months ago
2001
We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions. These models, which are built from shallow lingui...