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CEC
2011
IEEE
12 years 8 months ago
Stochastic Natural Gradient Descent by estimation of empirical covariances
—Stochastic relaxation aims at finding the minimum of a fitness function by identifying a proper sequence of distributions, in a given model, that minimize the expected value o...
Luigi Malagò, Matteo Matteucci, Giovanni Pi...
JGO
2010
117views more  JGO 2010»
13 years 7 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
BMCBI
2006
138views more  BMCBI 2006»
13 years 8 months ago
Approximation properties of haplotype tagging
Background: Single nucleotide polymorphisms (SNPs) are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns,...
Staal A. Vinterbo, Stephan Dreiseitl, Lucila Ohno-...
ROBOCOMM
2007
IEEE
14 years 3 months ago
Decentralized vehicle routing in a stochastic and dynamic environment with customer impatience
— Consider the following scenario: a spatio-temporal stochastic process generates service requests, localized at points in a bounded region on the plane; these service requests a...
Marco Pavone, Nabhendra Bisnik, Emilio Frazzoli, V...
EMSOFT
2007
Springer
14 years 21 days ago
A unified practical approach to stochastic DVS scheduling
This paper deals with energy-aware real-time system scheduling using dynamic voltage scaling (DVS) for energy-constrained embedded systems that execute variable and unpredictable ...
Ruibin Xu, Rami G. Melhem, Daniel Mossé