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Highly Cited

2011

Highly Cited

2011

Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling…

Highly Cited

2004

Highly Cited

2004

This article presents new results on using a greedy algorithm, orthogonal matching pursuit (OMP), to solve the sparse…

Highly Cited

2002

Highly Cited

2002

In k-means clustering we are given a set of n data points in d-dimensional space Rd and an integer k, and the problem is to…

Highly Cited

2001

Highly Cited

2001

Function estimation/approximation is viewed from the perspective of numerical optimization in function space, rather than…

Review

1997

Review

1997

Approximation algorithms have developed in response to the impossibility of solving a great variety of important optimization…

Highly Cited

1995

Highly Cited

1995

We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems…

Highly Cited

1993

Highly Cited

1993

The generalized assignment problem can be viewed as the following problem of scheduling parallel machines with costs. Each job is…

Highly Cited

1983

Highly Cited

1983

This paper describes a general technique that can be used to obtain approximation algorithms for various NP-complete problems on…

Highly Cited

1973

Highly Cited

1973

Simple, polynomial-time, heuristic algorithms for finding approximate solutions to various polynomial complete optimization…

Highly Cited

1973

Highly Cited

1973

This study presents the conditions of applicability of stochastic approximation algorithms that minimize a mean-square error…