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PRL
2007
180views more  PRL 2007»
15 years 1 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...
CPAIOR
2008
Springer
15 years 3 months ago
Amsaa: A Multistep Anticipatory Algorithm for Online Stochastic Combinatorial Optimization
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
Luc Mercier, Pascal Van Hentenryck
CEC
2010
IEEE
15 years 2 months ago
An analysis of clustering objectives for feature selection applied to encrypted traffic identification
This work explores the use of clustering objectives in a Multi-Objective Genetic Algorithm (MOGA) for both, feature selection and cluster count optimization, under the application...
Carlos Bacquet, A. Nur Zincir-Heywood, Malcolm I. ...
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SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
15 years 3 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
ICML
2008
IEEE
16 years 2 months ago
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
We show that linear value-function approximation is equivalent to a form of linear model approximation. We then derive a relationship between the model-approximation error and the...
Ronald Parr, Lihong Li, Gavin Taylor, Christopher ...