1. March 2023
Grateful to receive a grant from DSO National Laboratories.
27. February 2023
Two papers accepted in CVPR’23.
16. February 2023
Three papers accepted in ICASSP’23.
11. February 2023
CVPR’23 tutorial on Reverse Engineering of Deception: Foundations and Applications is accepted and will be given with Xiaoming Liu (MSU) and Xue Lin (Northeastern).
09. February 2023
AAAI’23 tutorial on Bi-level Optimization in ML: Foundations and Applications is now available!
20. January 2023
Four papers accepted in ICLR 2023: Issues and Fixes in IRM, TextGrad: Differentiable Solution to NLP Attack Generation, Provable Benefits of Sparse GNN, Sample Complexity Analysis of ViT
17. December 2022
One paper accepted in ASPDAC 2023: Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices.
17. December 2022
One paper accepted in SANER 2023: Towards Both Robust and Accurate Code Models; Equally contributed by Jinghan Jia (MSU) and Shashank Srikant (MIT).
23. November 2022
Code Repositories of Bi-Level Pruning (NeurIPS’22), Fairness Reprogramming (NeurIPS’22), and Visual Prompting by Iterative Label Mapping (arXiv) have been released.
22. November 2022
Dr. Sijia Liu is selected as a presenter of the AAAI 2023 New Faculty Highlight Program.
12. October 2022
Tutorial on Foundational Robustness of Foundation Models will be given in NeurIPS’22.
11. October 2022
Tutorial on Bi-level Machine Learning will be given in AAAI’23.
14. September 2022
Two papers accpeted in NeurIPS’22.
2. September 2022
Francesco Croce will give an invited talk on test-time defense on Sept. 7th.
31. August 2022
Dr. Sijia Liu is grateful to receive a Robust Intelligence (RI) Core Small Grant Award from NSF as the PI.
4. August 2022
Grateful to receive the Best Paper Runner-Up Award at UAI’22 in recognition of our work Distributed Adversarial Training to Robustify Deep Neural Networks at Scale.
16. May 2022
One paper accepted in UAI’22.
15. May 2022
Five papers accepted in ICML’22 : Bi-level adversarial training ; Winning lottery tickets from robust pretraining; Pruning helps certified robustness; Contrastive learning theory; and Generalization theory of GCN.
20. April 2022
One paper accepted in IJCAI’22.
1. April 2022
CFP: The 1st Workshop on New Frontiers in Adversarial Machine Learning at ICML’22 (AdvML-Frontiers@ICML’22).
11. March 2022
Dr. Sijia Liu is grateful to receive a gift funding from Cisco Research as the PI.
4. March 2022
Two papers accepted in CVPR’22. Congratulations to Yihua Zhang for his first CVPR paper!
28. February 2022
Aochuan(Arthur) Chen will join us in Fall 2022 – welcome Arthur!
21. January 2022
Five accepted papers in ICLR’22, Reverse Engineering of Adversaries, Black-Box Defense(spotlight), Learning to Optimize, Self-Training Theory, Distributed Learning. Congratulations to Yimeng Zhang, Yuguang Yao, Jianghan Jia for their first ICLR papers!
15. January 2022
Our work on interpreting and advancing adversarial training via bi-level optimization is now available on arXiv; equally contributed by Yihua Zhang (MSU) and Guanhua Zhang (UCSB).
15. October 2021
Dr. Sijia Liu receives a DARPA IP2 AIE Grant as a Co-PI.
28. September 2021
Five papers accepted in NeurIPS’21.
19. May 2021
Our MSU-NEU team (with PI Xiaoming Liu and co-PI Xue Lin) entered the Phase 2 of DARPA AIE RED.
13. May 2021
One paper accepted in ICML’21