ICML 2023 Workshop AdvML-Frontiers Submissions

Scoring Black-Box Models for Adversarial Robustness
Jian Vora, Pranay Reddy Samala
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
When Can Linear Learners be Robust to Indiscriminate Poisoning Attacks?
Fnu Suya, Xiao Zhang, Yuan Tian, David Evans
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Context-Aware Self-Adaptation for Domain Generalization
Hao Yan, Yuhong Guo
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Label Noise: Correcting a Correction Loss
William Toner, Amos Storkey
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Robust Semantic Segmentation: Strong Adversarial Attacks and Fast Training of Robust Models
Francesco Croce, Naman Deep Singh, Matthias Hein
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Model-tuning Via Prompts Makes NLP Models Adversarially Robust
Mrigank Raman, Pratyush Maini, J Zico Kolter, Zachary Chase Lipton, Danish Pruthi
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
Suraj Srinivas, Sebastian Bordt, Himabindu Lakkaraju
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Refined and Enriched Physics-based Captions for Unseen Dynamic Changes
HIDETOMO SAKAINO
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Adaptive Certified Training: Towards Better Accuracy-Robustness Tradeoffs
Zhakshylyk Nurlanov, Frank R. Schmidt, Florian Bernard
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Illusory Attacks: Detectability Matters in Adversarial Attacks on Sequential Decision-Makers
Tim Franzmeyer, Stephen Marcus McAleer, Joao F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schroeder de Witt
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Certified Calibration: Bounding Worst-Case Calibration under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip Torr, Adel Bibi
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Don't trust your eyes: on the (un)reliability of feature visualizations
Robert Geirhos, Roland S. Zimmermann, Blair Bilodeau, Wieland Brendel, Been Kim
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Classifier Robustness Enhancement Via Test-Time Transformation
Tsachi Blau, Roy Ganz, Chaim Baskin, Michael Elad, Alex M. Bronstein
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
CertViT: Certified Robustness of Pre-Trained Vision Transformers
Kavya Gupta, Sagar Verma
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Transferable Adversarial Perturbations between Self-Supervised Speech Recognition Models
Raphael Olivier, Hadi Abdullah, Bhiksha Raj
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Tunable Dual-Objective GANs for Stable Training
Monica Welfert, Kyle Otstot, Gowtham Raghunath Kurri, Lalitha Sankar
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
MLSMM: Machine Learning Security Maturity Model
Felix Viktor Jedrzejewski, Davide Fucci, Oleksandr Adamov
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Adversarial Training Should Be Cast as a Non-Zero-Sum Game
Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Unsupervised Adversarial Detection without Extra Model: Training Loss Should Change
Chien Cheng Chyou, Hung-Ting Su, Winston H. Hsu
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Stabilizing GNN for Fairness via Lipschitz Bounds
Yaning Jia, Chunhui Zhang
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Equal Long-term Benefit Rate: Adapting Static Fairness Notions to Sequential Decision Making
Yuancheng Xu, Chenghao Deng, Yanchao Sun, Ruijie Zheng, Xiyao Wang, Jieyu Zhao, Furong Huang
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks
Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
Certifying Ensembles: A General Certification Theory with S-Lipschitzness
Aleksandar Petrov, Francisco Eiras, Amartya Sanyal, Philip Torr, Adel Bibi
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
On the Limitations of Model Stealing with Uncertainty Quantification Models
David Pape, Sina Däubener, Thorsten Eisenhofer, Antonio Emanuele Cinà, Lea Schönherr
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone
The Challenge of Differentially Private Screening Rules
Amol Khanna, Fred Lu, Edward Raff
- Published: 20 Jun 2023, Last Modified: 07 Aug 2023
- AdvML-Frontiers 2023
- Readers: Everyone