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» A Bayesian Approach to Tackling Hard Computational Problems
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IPPS
2009
IEEE
14 years 5 months ago
Robust sequential resource allocation in heterogeneous distributed systems with random compute node failures
—The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of comp...
Vladimir Shestak, Edwin K. P. Chong, Anthony A. Ma...
AAAI
2008
14 years 22 days ago
Computing Minimal Diagnoses by Greedy Stochastic Search
Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are P 2 hard. To overc...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
RECOMB
2003
Springer
14 years 10 months ago
Joint classifier and feature optimization for cancer diagnosis using gene expression data
Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression pro...
Balaji Krishnapuram, Lawrence Carin, Alexander J. ...
TMI
2010
175views more  TMI 2010»
13 years 5 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
14 years 4 months ago
Quick-and-dirty ant colony optimization
Ant colony optimization (ACO) is a well known metaheuristic. In the literature it has been used for tackling many optimization problems. Often, ACO is hybridized with a local sear...
Paola Pellegrini, Elena Moretti