Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Given a graph (directed or undirected) with costs on the edges, and an integer k, we consider the problem of nding a k-node connected spanning subgraph of minimum cost. For the ge...
Abstract. Shop scheduling problems are known to be notoriously intractable, both in theory and practice. In this paper we give a randomized approximation algorithm for flow shop s...
We introduce a new problem in the study of doubling spaces: Given a point set S and a target dimension d , remove from S the fewest number of points so that the remaining set has d...
We give a (1 - 1/e)-approximation algorithm for the Max-Profit Generalized Assignment Problem (Max-GAP) with fixed profits when the profit (but not necessarily the size) of every ...