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...
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...
—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...
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...
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...