A review paper on nonconvex optimization is releasedThe paper, titled From Symmetry to Geometry: Tractable Nonconvex Problems, reviews recent advances on nonconvex optimization from a geometric perspective and landscape studies. This is a joint work with Yuqian Zhang and John Wright.
New paper submissionThe paper, titled Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization, is submitted. This is a joint work with Chong You, Zhihui Zhu, and Yi Ma.
Invited to be a speaker and organizer for Efficient Tensor Representations for Learning and Computational ComplexityThe workshop will be held from May 17 – 21, 2021 at the Institute for Pure and Applied Mathematics (IPAM) situated on the UCLA campus. This workshop is part of a semester long program on Tensor Methods and Emerging Applications to the Physical and Data Sciences.
A new review paper has been submitted to IEEE Signal Processing MagazineThe paper, titled Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications, reviews recent work on nonconvex optimization methods for finding the sparsest vectors in linear subspaces. This is a joint work with Zhihui Zhu, Xiao Li, Manolis Tsakiris, John Wright and Rene Vidal.
Two papers have been accepted at ICLR’20, with one oral presentation (top 1.85%)Our paper, titled Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning has been accepted at ICLR’20 as oral (top 1.85%). Our paper, titled Short-and-Sparse Deconvolution – A Geometric Approach has been accepted at ICLR’20 as poster (acceptance rate 26.5%).
One paper has been accepted at NeurIPS’19 as spotlight (top 3%)Our paper, titled A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution, has been accepted at NeurIPS’19 as spotlight (top 3%). This is a joint work with Xiao Li and Zhihui Zhu.
I have been recognized as one of the best reviewers at NeurIPS’19, and invited as a mentor to the first new in ML workshop at NeurIPS