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ICML
2005
IEEE
14 years 9 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
AROBOTS
1999
87views more  AROBOTS 1999»
13 years 8 months ago
Dynamics of a Classical Conditioning Model
Abstract. Classical conditioning is a basic learning mechanism in animals and can be found in almost all organisms. If we want to construct robots with abilities matching those of ...
Christian Balkenius
ICML
2008
IEEE
14 years 9 months ago
Gaussian process product models for nonparametric nonstationarity
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
Ryan Prescott Adams, Oliver Stegle
BMCBI
2008
138views more  BMCBI 2008»
13 years 8 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
AI
2002
Springer
13 years 8 months ago
Improving heuristic mini-max search by supervised learning
This article surveys three techniques for enhancing heuristic game-tree search pioneered in the author's Othello program Logistello, which dominated the computer Othello scen...
Michael Buro