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» Adaptive Algorithms for Online Decision Problems
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GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
ITA
2006
13 years 7 months ago
Decision problems among the main subfamilies of rational relations
We consider the four families of recognizable, synchronous, deterministic rational and rational subsets of a direct product of free monoids. They form a strict hierarchy and we in...
Olivier Carton, Christian Choffrut, Serge Grigorie...
SAC
2005
ACM
14 years 1 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
WAOA
2005
Springer
104views Algorithms» more  WAOA 2005»
14 years 1 months ago
The Online Target Date Assignment Problem
Abstract. Many online problems encountered in real-life involve a twostage decision process: upon arrival of a new request, an irrevocable firststage decision (the assignment of a...
Stefan Heinz, Sven Oliver Krumke, Nicole Megow, J&...
NIPS
2008
13 years 9 months ago
From Online to Batch Learning with Cutoff-Averaging
We present cutoff averaging, a technique for converting any conservative online learning algorithm into a batch learning algorithm. Most online-to-batch conversion techniques work...
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