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119
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ICPR
2000
IEEE
15 years 8 months ago
Scaling-Up Support Vector Machines Using Boosting Algorithm
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
Dmitry Pavlov, Jianchang Mao, Byron Dom
CORR
2008
Springer
125views Education» more  CORR 2008»
15 years 3 months ago
Adversary lower bounds for nonadaptive quantum algorithms
We present two general methods for proving lower bounds on the query complexity of nonadaptive quantum algorithms. Both methods are based on the adversary method of Ambainis. We sh...
Pascal Koiran, Jürgen Landes, Natacha Portier...
98
Voted
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 7 months ago
Evolutionary search for optimal combinations of markers in clothing manufacturing
Optimizing combinations of placements of parts, known as markers, is an important preparatory step in order-based industrial production of clothes. Given a work order in the form ...
Bogdan Filipic, Iztok Fister, Marjan Mernik
130
Voted
GECCO
2004
Springer
126views Optimization» more  GECCO 2004»
15 years 9 months ago
A Gene Based Adaptive Mutation Strategy for Genetic Algorithms
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
Sima Uyar, Sanem Sariel, Gülsen Eryigit
117
Voted
MOR
2006
81views more  MOR 2006»
15 years 3 months ago
Simulated Annealing for Convex Optimization
We apply the method known as simulated annealing to the following problem in convex optimization: minimize a linear function over an arbitrary convex set, where the convex set is ...
Adam Tauman Kalai, Santosh Vempala