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» Gadgets, Approximation, and Linear Programming
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ICML
2010
IEEE
13 years 11 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...
SODA
2004
ACM
161views Algorithms» more  SODA 2004»
13 years 11 months ago
Approximation schemes for Metric Bisection and partitioning
We design polynomial time approximation schemes (PTASs) for Metric BISECTION, i.e. dividing a given finite metric space into two halves so as to minimize or maximize the sum of di...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
TROB
2010
129views more  TROB 2010»
13 years 8 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...
MFCS
2005
Springer
14 years 3 months ago
Greedy Approximation via Duality for Packing, Combinatorial Auctions and Routing
We study simple greedy approximation algorithms for general class of integer packing problems. We provide a novel analysis based on the duality theory of linear programming. This e...
Piotr Krysta
DISOPT
2008
85views more  DISOPT 2008»
13 years 10 months ago
How tight is the corner relaxation?
Given a mixed-integer linear programming (MILP) model and an optimal basis of the associated linear programming relaxation, the Gomory's corner relaxation is obtained by drop...
Matteo Fischetti, Michele Monaci