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JMLR
2006
124views more  JMLR 2006»
13 years 8 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
EOR
2007
77views more  EOR 2007»
13 years 8 months ago
Solving the short-term electrical generation scheduling problem by an adaptive evolutionary approach
In this paper, we introduce an adaptive evolutionary approach to solve the short-term electrical generation scheduling problem (STEGS). The STEGS is a hard constraint satisfaction...
Jorge Maturana, María-Cristina Riff
PAA
2008
13 years 8 months ago
Prototype reduction using an artificial immune model
Artificial immune system (AIS)-based pattern classification approach is relatively new in the field of pattern recognition. The study explores the potentiality of this paradigm in ...
Utpal Garain
NN
2006
Springer
114views Neural Networks» more  NN 2006»
13 years 8 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
TCAD
2008
119views more  TCAD 2008»
13 years 8 months ago
FLUTE: Fast Lookup Table Based Rectilinear Steiner Minimal Tree Algorithm for VLSI Design
Abstract-- In this paper, we present a very fast and accurate rectilinear Steiner minimal tree (RSMT) algorithm called FLUTE. FLUTE is based on pre-computed lookup table to make RS...
Chris C. N. Chu, Yiu-Chung Wong