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KSEM
2009
Springer
14 years 4 days ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
BMCBI
2008
170views more  BMCBI 2008»
13 years 5 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
Loris Nanni, Alessandra Lumini
NIPS
2007
13 years 7 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
EMO
2001
Springer
109views Optimization» more  EMO 2001»
13 years 10 months ago
Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms
When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropri...
Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen
WIOPT
2011
IEEE
12 years 9 months ago
Network utility maximization over partially observable Markovian channels
Abstract—This paper considers maximizing throughput utility in a multi-user network with partially observable Markov ON/OFF channels. Instantaneous channel states are never known...
Chih-Ping Li, Michael J. Neely