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UAI
1998
15 years 7 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
EACL
1993
ACL Anthology
15 years 7 months ago
Data-Oriented Methods for Grapheme-to-Phoneme Conversion
It is traditionally assumed that various sources of linguistic knowledge and their interaction should be formalised in order to be able to convert words into their phonemic repres...
Antal van den Bosch, Walter Daelemans
IJCAI
1989
15 years 7 months ago
A Probabilistic Approach to Marker Propagation
Potentially, the advantages of marker-passing over local connectionist techniques for associa­ tive inference are (1) the ability to differen­ tiate variable bindings, and (2) r...
Dekai Wu
CIBCB
2009
IEEE
15 years 7 months ago
DDPIn - Distance and density based protein indexing
Protein structure similarity and classification methods have many applications in protein function prediction and associated fields (e.g. drug discovery). In this paper, we propose...
David Hoksza
GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
15 years 7 months ago
Self-adaptive constructivism in Neural XCS and XCSF
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
Gerard David Howard, Larry Bull, Pier Luca Lanzi