ICML 2023 Workshop AdvML-Frontiers Submissions

Theoretically Principled Trade-off for Stateful Defenses against Query-Based Black-Box Attacks
Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles
Chejian Xu, Ding Zhao, Alberto Sangiovanni-Vincentelli, Bo Li
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Improving Adversarial Training for Multiple Perturbations through the Lens of Uniform Stability
Jiancong Xiao, Zeyu Qin, Yanbo Fan, Baoyuan Wu, Jue Wang, Zhi-Quan Luo
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
A Theoretical Perspective on the Robustness of Feature Extractors
Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Characterizing the Optimal $0-1$ Loss for Multi-class Classification with a Test-time Attacker
Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao, Haitao Zheng, Prateek Mittal
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Rethinking Robust Contrastive Learning from the Adversarial Perspective
Fatemeh Ghofrani, Mehdi Yaghouti, Pooyan Jamshidi
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
TMI! Finetuned Models Spill Secrets from Pretraining
John Abascal, Stanley Wu, Alina Oprea, Jonathan Ullman
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
A First Order Meta Stackelberg Method for Robust Federated Learning
Yunian Pan, Tao Li, Henger Li, Tianyi Xu, Quanyan Zhu, Zizhan Zheng
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Backdoor Attacks for In-Context Learning with Language Models
Nikhil Kandpal, Matthew Jagielski, Florian Tramèr, Nicholas Carlini
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
R-LPIPS: An Adversarially Robust Perceptual Similarity Metric
Sara Ghazanfari, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Alexandre Araujo
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Risk-Averse Predictions on Unseen Domains via Neural Style Smoothing
Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
A Simple and Yet Fairly Effective Defense for Graph Neural Networks
Sofiane ENNADIR, Yassine ABBAHADDOU, Michalis Vazirgiannis, Henrik Boström
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Incentivizing Honesty among Competitors in Collaborative Learning
Florian E. Dorner, Nikola Konstantinov, Georgi Stoyanov Pashaliev, Martin Vechev
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Towards Effective Data Poisoning for Imbalanced Classification
Snigdha Sushil Mishra, Hao He, Hao Wang
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Black Box Adversarial Prompting for Foundation Models
Natalie Maus, Patrick Chao, Eric Wong, Jacob R. Gardner
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Exposing the Fake: Effective Diffusion-Generated Images Detection
RuiPeng Ma, Jinhao Duan, Fei Kong, Xiaoshuang Shi, Kaidi Xu
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
AdversNLP: A Practical Guide to Assessing NLP Robustness Against Text Adversarial Attacks
Othmane BELMOUKADAM
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Proximal Compositional Optimization for Distributionally Robust Learning
Prashant Khanduri, Chengyin Li, RAFI IBN SULTAN, Yao Qiang, Joerg Kliewer, Dongxiao Zhu
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
PIAT: Parameter Interpolation based Adversarial Training for Image Classification
Kun He, Xin Liu, Yichen Yang, Zhou Qin, Weigao Wen, Hui Xue', John E. Hopcroft
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Mathematical Theory of Adversarial Deep Learning
Xiao-Shan Gao, Lijia Yu, Shuang Liu
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Tuomas Sandholm, Furong Huang, Stephen Marcus McAleer
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Navigating Graph Robust Learning against All-Intensity Attacks
Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Chuxu Zhang
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Towards Out-of-Distribution Adversarial Robustness
Adam Ibrahim, Charles Guille-Escuret, Ioannis Mitliagkas, Irina Rish, David Krueger, Pouya Bashivan
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
Hyeonjeong Ha, Minseon Kim, Sung Ju Hwang
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Adversarial Robustness for Tabular Data through Cost and Utility Awareness
Klim Kireev, Bogdan Kulynych, Carmela Troncoso
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone