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129965 |
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|a Bertsimas, Dimitris J
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|a Sloan School of Management
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|a Massachusetts Institute of Technology. Operations Research Center
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|a Cory-Wright, Ryan
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|a On polyhedral and second-order cone decompositions of semidefinite optimization problems
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|b Elsevier BV,
|c 2021-02-22T21:52:59Z.
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|z Get fulltext
|u https://hdl.handle.net/1721.1/129965
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|a We study a cutting-plane method for semidefinite optimization problems, and supply a proof of the method's convergence, under a boundedness assumption. By relating the method's rate of convergence to an initial outer approximation's diameter, we argue the method performs well when initialized with a second-order cone approximation, instead of a linear approximation. We invoke the method to provide bound gaps of 0.5-6.5% for sparse PCA problems with 1000s of covariates, and solve nuclear norm problems over 500 × 500 matrices.
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|a en
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|a Article
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|t Operations Research Letters
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