Decomposition-based Pareto optimization for subset selection
نویسندگان
چکیده
منابع مشابه
Subset Selection by Pareto Optimization
Selecting the optimal subset from a large set of variables is a fundamental problem in various learning tasks such as feature selection, sparse regression, dictionary learning, etc. In this paper, we propose the POSS approach which employs evolutionary Pareto optimization to find a small-sized subset with good performance. We prove that for sparse regression, POSS is able to achieve the best-so...
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Subset selection that selects a few variables from a large set is a fundamental problem in many areas. The recently emerged Pareto Optimization for Subset Selection (POSS) method is a powerful approximation solver for this problem. However, POSS is not readily parallelizable, restricting its large-scale applications on modern computing architectures. In this paper, we propose PPOSS, a parallel ...
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The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that ut...
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Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
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ژورنال
عنوان ژورنال: SCIENTIA SINICA Informationis
سال: 2016
ISSN: 1674-7267
DOI: 10.1360/n112016-00045