22. September 2023
NeurIPS 2023: 3 Papers Accepted – 1 Spotlight and 2 Posters. Congratulations to Jinghan, Jiancheng, and Yuguang for their spotlight acceptance with ‘Model Sparsity Simplifies Machine Unlearning’. And kudos to Yihua, Yimeng, Aochuan, Jinghan, and Jiancheng for their poster acceptance with ‘Selectivity Boosts Transfer Learning Efficiency.’
31. August 2023
Grateful to receive a grant from Army Research Office (ARO) as the PI.
12. August 2023
Our paper on Adversarial Training for MoE has been chosen for an Oral Presentation at ICCV’23!
2. August 2023
Grateful to receive a gift funding from Cisco Research as the PI.
21. July 2023
Call for participation in 2nd AdvML-Frontiers Workshop@ICML’23
19. July 2023
One paper in ICCV’23 on Adversarial Robustness of Mixture-of-Experts
29. June 2023
Grateful to receive a CPS Medium Grant Award from NSF as a co-PI.
4. June 2023
Our paper Visual Prompting for Adversarial Robustness received the Top 3% Paper Recognition at ICASSP 2023. Congrats to Aochuan, Peter (internship at OPTML in 2022), Yuguang, and Pin-Yu (IBM Research)!
13. April 2023
Grateful to receive a grant from Lawrence Livermore National Laboratory.
1. April 2023
Call for Papers and AdvML Rising Star Award Applications in the workshop AdvML-Frontiers, ICML’23
17. March 2023
A new arXiv paper is released: Adversarial attacks can be parsed to reveal victim model information! (see [Paper])
17. March 2023
The 2nd Workshop on New Frontiers in Adversarial Machine Learning has been accepted by ICML’23
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.
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.
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.
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.
13. May 2021
One paper accepted in ICML’21