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SAT
2009
Springer
111views Hardware» more  SAT 2009»
15 years 10 months ago
Restart Strategy Selection Using Machine Learning Techniques
Abstract. Restart strategies are an important factor in the performance of conflict-driven Davis Putnam style SAT solvers. Selecting a good restart strategy for a problem instance...
Shai Haim, Toby Walsh
131
Voted
JMLR
2010
108views more  JMLR 2010»
14 years 10 months ago
Feature Selection using Multiple Streams
Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes wh...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
157
Voted
CIVR
2007
Springer
192views Image Analysis» more  CIVR 2007»
15 years 10 months ago
Texture retrieval based on a non-parametric measure for multivariate distributions
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...
ECCV
2008
Springer
16 years 5 months ago
CSDD Features: Center-Surround Distribution Distance for Feature Extraction and Matching
Abstract. We present an interest region operator and feature descriptor called Center-Surround Distribution Distance (CSDD) that is based on comparing feature distributions between...
Robert T. Collins, Weina Ge
131
Voted
ESANN
2006
15 years 5 months ago
On the selection of hidden neurons with heuristic search strategies for approximation
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Ignacio Barrio, Enrique Romero, Lluís A. Be...