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Abstract: s 1963 by Bellman and Fan [2]. They also observed that duality theorems require somewhat stronger assumptions for SDP than for LP: specifically, they used a Slater-type constraint qualification to guarantee a zero duality gap. ffl Interior-point methods: SDP can be very effectively solved by generalizing interiorpoint methods developed originally for LP. The credit for this important discovery goes primarily to Nesterov and Nemirovski [9] (who gave a far-reaching theory for general convex... (Update)
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BibTeX entry: (Update)
@misc{ overton-foreword,
author = "Michael Overton and Henry Wolkowicz",
title = "Foreword: for Special Issue on Semidefinite Programming",
url = "citeseer.ist.psu.edu/81694.html" }
Citations (may not include all citations):529 Linear Matrix Inequalities in System and Control Theory (context) - BOYD, GHAOUI et al. - 1994
326 Interior Point Polynomial Algorithms in Convex Programming (context) - NESTEROV, NEMIROVSKII - 1994
276 Semidefinite programming - VANDENBERGHE, BOYD - 1996 ACM
134 Geometric Algorithms and Combinatorial Optimization (context) - OTSCHEL, LOV et al. - 1988
72 Cones of matrices and set-functions and 0-1 optimization (context) - LOV, SCHRIJVER - 1991
60 Combinatorial optimization with interior point methods and s.. (context) - ALIZADEH - 1991
57 Eigenvalue optimization - LEWIS, OVERTON - 1996
29 The minimization of certain nondifferentiable sums of eigenv.. (context) - CULLUM, DONATH et al. - 1975
11 On systems of linear inequalities in Hermitian matrix variab.. (context) - BELLMAN, FAN - 1963
10 Characterization of the barrier parameter of homogeneous con.. - GULER, TUNCEL - 1995 ACM
1 Survey of semidefinite relaxations for discrete optimization (context) - PARDALOS, RENDL et al.
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