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20172026
most citedSketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage

62 citations · 87 across the 19 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

math.OC2019

Scalable Semidefinite Programming

Alp Yurtsever, Joel A. Tropp, Olivier Fercoq +2

Semidefinite programming (SDP) is a powerful framework from convex optimization that has striking potential for data science applications. This paper develops a provably correct ra…

math.OC2019

Inertial Three-Operator Splitting Method and Applications

Volkan Cevher, Bang Cong Vu, Alp Yurtsever

We introduce an inertial variant of the forward-Douglas-Rachford splitting and analyze its convergence. We specify an instance of the proposed method to the three-composite convex…

math.OC2019

An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity

Lijun Ding, Alp Yurtsever, Volkan Cevher +2

This paper develops a new storage-optimal algorithm that provably solves generic semidefinite programs (SDPs) in standard form. This method is particularly effective for weakly con…

math.OC201911 cited

A Conditional Gradient-Based Augmented Lagrangian Framework

Alp Yurtsever, Olivier Fercoq, Volkan Cevher

This paper considers a generic convex minimization template with affine constraints over a compact domain, which covers key semidefinite programming applications. The existing cond…

math.OC2019

Stochastic Frank-Wolfe for Composite Convex Minimization

Francesco Locatello, Alp Yurtsever, Olivier Fercoq +1

A broad class of convex optimization problems can be formulated as a semidefinite program (SDP), minimization of a convex function over the positive-semidefinite cone subject to so…