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» Learning relational dependency networks in hybrid domains
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NIPS
2004
14 years 5 days ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
JMLR
2006
153views more  JMLR 2006»
13 years 10 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
DAWAK
2006
Springer
14 years 2 months ago
Learning Classifiers from Distributed, Ontology-Extended Data Sources
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
Doina Caragea, Jun Zhang 0002, Jyotishman Pathak, ...
NIPS
1997
14 years 4 days ago
Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report
Singular value decomposition (SVD) can be viewed as a method for unsupervised training of a network that associates two classes of events reciprocally by linear connections throug...
Thomas K. Landauer, Darrell Laham, Peter W. Foltz
IJCAI
2007
14 years 6 days ago
Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks
Coronary Heart Disease can be diagnosed by measuring and scoring regional motion of the heart wall in ultrasound images of the left ventricle (LV) of the heart. We describe a comp...
Maleeha Qazi, Glenn Fung, Sriram Krishnan, R&oacut...