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AAAI
2006
14 years 11 months ago
Exploring GnuGo's Evaluation Function with a SVM
While computers have defeated the best human players in many classic board games, progress in Go remains elusive. The large branching factor in the game makes traditional adversar...
Christopher Fellows, Yuri Malitsky, Gregory Wojtas...
NPL
2006
109views more  NPL 2006»
14 years 9 months ago
CB3: An Adaptive Error Function for Backpropagation Training
Effective backpropagation training of multi-layer perceptrons depends on the incorporation of an appropriate error or objective function. Classification-based (CB) error functions ...
Michael Rimer, Tony Martinez
JSW
2007
126views more  JSW 2007»
14 years 9 months ago
Efficient Evaluation of Multiple-Output Boolean Functions in Embedded Software or Firmware
— The paper addresses software and firmware implementation of multiple-output Boolean functions based on cascades of Look-Up Tables (LUTs). A LUT cascade is described as a means ...
Vaclav Dvorak
RC
2007
83views more  RC 2007»
14 years 9 months ago
Computing the Pessimism of Inclusion Functions
Abstract. “Computing the pessimism” means bounding the overestimation produced by an inclusion function. There are two important distinctions with classical error analysis. Fir...
Gilles Chabert, Luc Jaulin
95
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INCDM
2010
Springer
138views Data Mining» more  INCDM 2010»
14 years 8 months ago
Learning Discriminative Distance Functions for Case Retrieval and Decision Support
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Alexey Tsymbal, Martin Huber, Shaohua Kevin Zhou