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» Feature Selection in Clustering Problems
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ICPR
2010
IEEE
13 years 10 months ago
Improved Mean Shift Algorithm with Heterogeneous Node Weights
The conventional mean shift algorithm has been known to be sensitive to selecting a bandwidth. We present a robust mean shift algorithm with heterogeneous node weights that come f...
Ji Won Yoon, Simon P. Wilson
ECML
2007
Springer
14 years 4 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
14 years 1 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock
HIS
2009
13 years 8 months ago
A Swarm-Based Rough Set Approach for Group Decision Support Systems
This paper present a class of investment problem, in which many items could be chosen in a group decision environment. Usually there is a decision table from the board of director...
Mingyan Zhao, Hongbo Liu, Ajith Abraham, Emilio Co...
CVPR
2005
IEEE
15 years 6 days ago
A Sparse Support Vector Machine Approach to Region-Based Image Categorization
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Jinbo Bi, Yixin Chen, James Ze Wang