OPTML-Group/Fast-BAT OPTML-Group/Fast-BAT

  • Stars
    star
    72
  • Rank 435,859 (Top 9 %)
  • Language
    Shell
  • Created over 2 years ago
  • Updated almost 2 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
OPTML-Group/Fast-BAT
github

OPTML-Group

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

[ICML22] "Revisiting and Advancing Fast Adversarial Training through the Lens of Bi-level Optimization" by Yihua Zhang*, Guanhua Zhang*, Prashant Khanduri, Mingyi Hong, Shiyu Chang, and Sijia Liu

More Repositories

1

BiP

[NeurIPS22] "Advancing Model Pruning via Bi-level Optimization" by Yihua Zhang*, Yuguang Yao*, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, and Sijia Liu
Python
141
star
2

Unlearn-Saliency

[ICLR24 (Spotlight)] "SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation" by Chongyu Fan*, Jiancheng Liu*, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
Python
79
star
3

Unlearn-Sparse

[NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
Python
60
star
4

ILM-VP

[CVPR23] "Understanding and Improving Visual Prompting: A Label-Mapping Perspective" by Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, and Sijia Liu
Python
50
star
5

Diffusion-MU-Attack

The official implementation of ECCV'24 paper "To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now". This work introduces one fast and effective attack method to evaluate the harmful-content generation ability of safety-driven unlearned diffusion models.
Python
38
star
6

DeepZero

[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
Python
35
star
7

AdvUnlearn

Official implementation of "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models"
Jupyter Notebook
14
star
8

RED-adv

"Can Adversarial Examples Be Parsed to Reveal Victim Model Information?" by Yuguang Yao*, Jiancheng Liu*, Yifan Gong*, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu
Python
7
star
9

CLAW-SAT

Code repository for the SANER 2023 paper CLAWSAT: Towards Both Robust and Accurate Code Models.
Python
4
star
10

Black-Box-Defense

[ICLR22] "How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective" by Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
Python
4
star
11

RED-ICLR22

[ICLR22] "Reverse Engineering of Imperceptible Adversarial Image Perturbations" by Yifan Gong*, Yuguang Yao*, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu
Python
4
star
12

Robust-MoE-CNN

[ICCV23] Robust Mixture-of-Expert Training for Convolutional Neural Networks by Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang (Atlas) Wang, Sijia Liu
Python
3
star
13

Fairness-Reprogramming

[NeurIPS 22] "Fairness Reprogramming" by Guanhua Zhang*, Yihua Zhang*, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
Python
2
star
14

OPTML-Group.github.io

SCSS
1
star
15

BackdoorMSPC

[ICLR2024]"Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency" by Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu
Python
1
star