In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
We analyze the addition of a simple local improvement step to various known randomized approximation algorithms. Let ' 0:87856 denote the best approximation ratio currently k...
We propose approximation algorithms under game-theoretic considerations. We indroduce and study the general covering problem which is a natural generalization of the well-studied m...
One challenge faced by many Inductive Logic Programming (ILP) systems is poor scalability to problems with large search spaces and many examples. Randomized search methods such as ...
Given an undirected multigraph G and a subset of vertices S V (G), the STEINER TREE PACKING problem is to find a largest collection of edge-disjoint trees that each connects S. T...