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» Solving Demodulation as an Optimization Problem
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ICML
2010
IEEE
15 years 5 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
ICCV
2009
IEEE
16 years 9 months ago
Efficient Discriminative Learning of Parts-based Models
Supervised learning of a parts-based model can be for- mulated as an optimization problem with a large (exponen- tial in the number of parts) set of constraints. We show how thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
LION
2009
Springer
115views Optimization» more  LION 2009»
15 years 11 months ago
Flexible Stochastic Local Search for Haplotype Inference
Abstract. Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genoty...
Luca Di Gaspero, Andrea Roli
COMPSAC
2004
IEEE
15 years 8 months ago
A Development Framework for Rapid Meta-Heuristics Hybridization
While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to speci...
Hoong Chuin Lau, Wee Chong Wan, Min Kwang Lim, Ste...
JAIR
2010
115views more  JAIR 2010»
15 years 3 months ago
An Investigation into Mathematical Programming for Finite Horizon Decentralized POMDPs
Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
Raghav Aras, Alain Dutech