[Nov 26, 2022] To be a Reviewer for 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023).
[Nov 10, 2022] Our tutorial proposal Deep Learning with Nontrivial Constraints has been accepted to SIAM International Conference on Data Mining (SDM23) Tutorial Program as a two-hour tutorial!
[Oct 20, 2022] Our paper NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning has been accepted by Neural Information Processing Systems (NeurIPS) Workshop on Optimization for Machine Learning (OPT 2022), see our poster for more details!
[Oct 20, 2022] Our paper Optimization for Robustness Evaluation beyond ℓp Metrics has been accepted by Neural Information Processing Systems (NeurIPS) Workshop on Optimization for Machine Learning (OPT 2022), see our poster for more details!
[Oct 03, 2022] Proud to release our paper NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning on arXiv! This is an expanded version of our previous announcement paper, with four detailed examples on constrained deep learning.
[Oct 03, 2022] Proud to release our paper Optimization for Robustness Evaluation beyond ℓp Metrics on arXiv! This is a preview of our ongoing project that numerically solves adversarial attack problems with general metrics (vs SOTA that only deals with ℓ1, ℓ2, and ℓ∞), taking advantage of our NCVX framework.
[Sep 19, 2022] To be a Reviewer for the 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023).
[Jul 27, 2022] We (speaker: Prof. Ju Sun) introduced NCVX PyGRANSO and its practical applications and tricks in the Nonsmooth Optimization in Machine Learning session in the International Conference on Continuous Optimization (ICCOPT), 2022. See the talk slides for more details!
[May 29, 2022] I am funded by the FAIR4HEP Grant to make FAIR (Findable, Accessible, Interoperable, and Reusable) AI models for high-energy physics data.
[Jan 07, 2022] Our NCVX package is highlighted in Research Computing (Office of the Vice President for Research)
[Nov 29, 2021] Proud to release our paper NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning on arXiv! NCVX is the initial translation and revamping of the GRANSO package, with convenient features such as auto-differentiation and GPU support. In particular, NCVX can be used to solve constrained deep learning problems.
[May 25, 2021] I am funded by the U of M Informatics Institute (UMII) Seed Grant Program to revamp the GRANSO package into a user-friendly, scalable numerical optimization package.