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NIPS
1998
15 years 8 months ago
Approximate Learning of Dynamic Models
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 ...
Xavier Boyen, Daphne Koller
APPROX
2000
Springer
190views Algorithms» more  APPROX 2000»
15 years 11 months ago
Approximating node connectivity problems via set covers
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...
Guy Kortsarz, Zeev Nutov
FSTTCS
1999
Springer
15 years 11 months ago
A Randomized Algorithm for Flow Shop Scheduling
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...
Naveen Garg, Sachin Jain, Chaitanya Swamy
APPROX
2010
Springer
160views Algorithms» more  APPROX 2010»
15 years 6 months ago
Proximity Algorithms for Nearly-Doubling Spaces
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...
Lee-Ad Gottlieb, Robert Krauthgamer
ORL
2006
114views more  ORL 2006»
15 years 6 months ago
A (1-1/e)-approximation algorithm for the generalized assignment problem
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 ...
Zeev Nutov, Israel Beniaminy, Raphael Yuster