38 citations · 48 across the 4 of their papers we have counts for
6 papers · 1 filter
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery
Lijun Ding, Liwei Jiang, Yudong Chen +2
We study the robust recovery of a low-rank matrix from sparsely and grossly corrupted Gaussian measurements, with no prior knowledge on the intrinsic rank. We consider the robust m…
Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
Lijun Ding, Yingjie Fei, Qiantong Xu +1
We develop a novel variant of the classical Frank-Wolfe algorithm, which we call spectral Frank-Wolfe, for convex optimization over a spectrahedron. The spectral Frank-Wolfe algori…
Bundle Method Sketching for Low Rank Semidefinite Programming
Lijun Ding, Benjamin Grimmer
In this paper, we show that the bundle method can be applied to solve semidefinite programming problems with a low rank solution without ever constructing a full matrix. To accompl…
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…
Higher-Order Cone Programming
Lijun Ding, Lek-Heng Lim
We introduce a conic embedding condition that gives a hierarchy of cones and cone programs. This condition is satisfied by a large number of convex cones including the cone of copo…
Frank-Wolfe Style Algorithms for Large Scale Optimization
Lijun Ding, Madeleine Udell
We introduce a few variants on Frank-Wolfe style algorithms suitable for large scale optimization. We show how to modify the standard Frank-Wolfe algorithm using stochastic gradien…