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164
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GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 7 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
133
Voted
GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
15 years 4 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
122
Voted
ICPR
2002
IEEE
16 years 4 months ago
Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning
A heretofore unsolved problem of great archaeological importance is the automatic assembly of pots made on a wheel from the hundreds (or thousands) of sherds found at an excavatio...
David B. Cooper, Andrew R. Willis, Stuart Andrews,...
122
Voted
BROADNETS
2005
IEEE
15 years 9 months ago
Multi-rate throughput optimization for wireless local area network anomaly problem
— Due to varying wireless channel conditions, the IEEE 802.11 wireless local area network (WLAN) standard supports multiple modulation types to accommodate the tradeoff between d...
Yu-Liang Kuo, Kun-Wei Lai, Frank Yeong-Sung Lin, Y...
JGO
2010
117views more  JGO 2010»
15 years 2 months ago
Machine learning problems from optimization perspective
Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
Lei Xu