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» Finding Structure in Reinforcement Learning
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142
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BMCBI
2008
174views more  BMCBI 2008»
15 years 3 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
152
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KDD
2008
ACM
183views Data Mining» more  KDD 2008»
16 years 4 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
128
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LREC
2008
174views Education» more  LREC 2008»
15 years 5 months ago
UnsuParse: unsupervised Parsing with unsupervised Part of Speech Tagging
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...
Christian Hänig, Stefan Bordag, Uwe Quasthoff
UAI
2008
15 years 5 months ago
Learning Inclusion-Optimal Chordal Graphs
Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algo...
Vincent Auvray, Louis Wehenkel
120
Voted
NIPS
2001
15 years 5 months ago
Improvisation and Learning
This article presents a 2-phase computational learning model and application. As a demonstration, a system has been built, called CHIME for Computer Human Interacting Musical Enti...
Judy A. Franklin