My research lies at the intersection of optimization and statistics. You can check my google scholar for a full list of my work.  

Semidefinite programming

Revisiting Spectral Bundle Methods: Primal-dual (Sub)linear Convergence Rates [arxiv]  [slides]

Ding and Grimmer         

A Strict Complementarity Approach to Error Bound and Sensitivity of Solution of Conic Programs [arxiv]

Ding and Udell      

An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity [arxiv] [slides]

 Ding, Yurtsever, Cevher, Tropp, and Udell 

On the simplicity and conditioning of low rank semidefinite programs [arxiv

Ding and Udell                                                                                                

Higher-Order Cone Programming [arxiv] [slides]

Ding and Lim                  

Statistical nonconvex optimization

Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence [arxiv

Charisopoulos, Chen, Davis, Diaz, Ding, and Drusvyatskiy                   

Low-rank matrix recovery with non-quadratic loss: projected gradient method and regularity projection oracle [arxiv

Ding, Zhang, and Chen                                                         

Leave-one-out Approach for Matrix Completion: Primal and Dual Analysis [arxiv] [slides]

Ding and Chen                                                                                                   

Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery [arxiv] 

Fan, Ding, Chen, and Udell                                        



kFW: A Frank-Wolfe style algorithm with stronger subproblem oracles [arxiv] [slides]

Ding, Fan, and Udell 

Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence [arxiv]

Ding, Fei, Xu, and Yang                                                            

Frank-Wolfe Style Algorithms for Large Scale Optimization [arxiv]

Ding and Udell