51 Results

Poster
Tue 7:00 Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks
Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly
Poster
Tue 7:00 Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li
Poster
Tue 7:00 Accelerated Stochastic Gradient-free and Projection-free Methods
Feihu Huang, Lue Tao, Songcan Chen
Poster
Tue 7:00 Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Pranjal Awasthi, Natalie Frank, Mehryar Mohri
Poster
Tue 7:00 Towards Understanding the Dynamics of the First-Order Adversaries
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie Su
Poster
Tue 8:00 Parameterized Rate-Distortion Stochastic Encoder
Quan Hoang, Trung Le, Dinh Phung
Poster
Tue 8:00 Stronger and Faster Wasserstein Adversarial Attacks
Kaiwen Wu, Allen Wang, Yaoliang Yu
Poster
Tue 8:00 Adversarial Neural Pruning with Latent Vulnerability Suppression
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
Poster
Tue 8:00 Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources
Yun Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
Poster
Tue 8:00 Overfitting in adversarially robust deep learning
Leslie Rice, Eric Wong, Zico Kolter
Poster
Tue 9:00 Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions
Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil
Poster
Tue 9:00 Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Sicheng Zhu, Xiao Zhang, David Evans
Poster
Tue 9:00 Adversarial Attacks on Probabilistic Autoregressive Forecasting Models
Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin Vechev
Poster
Tue 10:00 When are Non-Parametric Methods Robust?
Robi Bhattacharjee, Kamalika Chaudhuri
Poster
Tue 11:00 Understanding and Mitigating the Tradeoff between Robustness and Accuracy
Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang
Poster
Tue 11:00 Adversarial Robustness for Code
Pavol Bielik, Martin Vechev
Poster
Tue 13:00 Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
David Stutz, Matthias Hein, Bernt Schiele
Poster
Tue 18:00 Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan Kankanhalli
Poster
Tue 18:00 Efficiently Learning Adversarially Robust Halfspaces with Noise
Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nati Srebro
Poster
Wed 5:00 Adversarial Risk via Optimal Transport and Optimal Couplings
Muni Sreenivas Pydi, Varun Jog
Poster
Wed 5:00 Second-Order Provable Defenses against Adversarial Attacks
Sahil Singla, Soheil Feizi
Poster
Wed 8:00 Black-box Certification and Learning under Adversarial Perturbations
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Poster
Wed 8:00 Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations
Florian Tramer, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn Jacobsen
Poster
Wed 8:00 Proper Network Interpretability Helps Adversarial Robustness in Classification
Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel
Poster
Wed 9:00 Adversarial Robustness Against the Union of Multiple Perturbation Models
Pratyush Maini, Eric Wong, Zico Kolter
Poster
Wed 9:00 Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability
Mingjie Li, Lingshen He, Zhouchen Lin
Poster
Wed 10:00 Hierarchical Verification for Adversarial Robustness
Cong Han Lim, Raquel Urtasun, Ersin Yumer
Poster
Wed 11:00 Fairwashing explanations with off-manifold detergent
Christopher Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-robert Mueller, Pan Kessel
Poster
Wed 12:00 Scalable Differential Privacy with Certified Robustness in Adversarial Learning
Hai Phan, My T. Thai, Han Hu, Ruoming Jin, Tong Sun, Dejing Dou
Poster
Wed 12:00 DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
Nathan Kallus
Poster
Wed 14:00 Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce, Matthias Hein
Poster
Wed 16:00 Adversarial Robustness via Runtime Masking and Cleansing
Yi-Hsuan Wu, Jimmy Yuan, Shan-Hung (Brandon) Wu
Poster
Wed 16:00 On Lp-norm Robustness of Ensemble Decision Stumps and Trees
Yihan Wang, Huan Zhang, Hongge Chen, Duane Boning, Cho-Jui Hsieh
Poster
Thu 6:00 Towards Understanding the Regularization of Adversarial Robustness on Neural Networks
Yuxin Wen, Shuai Li, Kui Jia
Poster
Thu 6:00 Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification
Chen Dan, Yuting Wei, Pradeep Ravikumar
Poster
Thu 6:00 On Breaking Deep Generative Model-based Defenses and Beyond
Yanzhi Chen, Renjie Xie, Zhanxing Zhu
Poster
Thu 6:00 Interpreting Robust Optimization via Adversarial Influence Functions
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Poster
Thu 6:00 Robustness to Programmable String Transformations via Augmented Abstract Training
Yuhao Zhang, Aws Albarghouthi, Loris D'Antoni
Poster
Thu 6:00 Concise Explanations of Neural Networks using Adversarial Training
PRASAD Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha
Poster
Thu 6:00 Improving Robustness of Deep-Learning-Based Image Reconstruction
Ankit Raj, Yoram Bresler, Bo Li
Poster
Thu 7:00 Adversarial Attacks on Copyright Detection Systems
Parsa Saadatpanah, Ali Shafahi, Tom Goldstein
Poster
Thu 7:00 More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models
Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi
Poster
Thu 8:00 Defense Through Diverse Directions
Christopher Bender, Yang Li, Yifeng Shi, Michael K. Reiter, Junier Oliva
Poster
Thu 12:00 Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann
Poster
Thu 12:00 Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce, Matthias Hein
Poster
Thu 13:00 Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
Fabian Latorre, Paul Rolland, Shaul Nadav Hallak, Volkan Cevher
Poster
Thu 15:00 Randomization matters How to defend against strong adversarial attacks
Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif
Poster
Thu 15:00 Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness
Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi
Poster
Thu 17:00 Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks
Yonggang Zhang, Ya Li, Tongliang Liu, Xinmei Tian
Workshop
Fri 6:45 What does it mean for ML to be trustworthy?
Nicolas Papernot
Workshop
Fri 9:00 Poster Session (click to see links)