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IJCNN
2006
IEEE
14 years 3 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley
GECCO
2010
Springer
181views Optimization» more  GECCO 2010»
14 years 1 months ago
Evolving neural networks in compressed weight space
We propose a new indirect encoding scheme for neural networks in which the weight matrices are represented in the frequency domain by sets of Fourier coefficients. This scheme exp...
Jan Koutnik, Faustino J. Gomez, Jürgen Schmid...
MVA
2007
154views Computer Vision» more  MVA 2007»
13 years 10 months ago
Fisher Non-negative Matrix Factorization with Pairwise Weighting
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...
Xi Li, Kazuhiro Fukui
ALGORITHMICA
2010
95views more  ALGORITHMICA 2010»
13 years 9 months ago
Homogeneous String Segmentation using Trees and Weighted Independent Sets
We divide a string into k segments, each with only one sort of symbols, so as to minimize the total number of exceptions. Motivations come from machine learning and data mining. F...
Peter Damaschke
SAT
2007
Springer
121views Hardware» more  SAT 2007»
14 years 3 months ago
MiniMaxSat: A New Weighted Max-SAT Solver
In this paper we introduce MINIMAXSAT, a new Max-SAT solver that incorporates the best SAT and Max-SAT techniques. It can handle hard clauses (clauses of mandatory satisfaction as ...
Federico Heras, Javier Larrosa, Albert Oliveras