Adversarially Robust PAC Learnability of Real-Valued Functions
Authors: Idan Attias, Steve Hanneke | Published: 2022-06-26 | Updated: 2024-05-05
Algorithm Design
Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising
Authors: Sandhya Aneja, Nagender Aneja, Pg Emeroylariffion Abas, Abdul Ghani Naim | Published: 2022-06-25
Using Autoencoders on Differentially Private Federated Learning GANs
Authors: Gregor Schram, Rui Wang, Kaitai Liang | Published: 2022-06-24
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Authors: Mark Huasong Meng, Guangdong Bai, Sin Gee Teo, Zhe Hou, Yan Xiao, Yun Lin, Jin Song Dong | Published: 2022-06-24 | Updated: 2022-10-11
“You Can’t Fix What You Can’t Measure”: Privately Measuring Demographic Performance Disparities in Federated Learning
Authors: Marc Juarez, Aleksandra Korolova | Published: 2022-06-24 | Updated: 2023-01-11
Authentication of Copy Detection Patterns under Machine Learning Attacks: A Supervised Approach
Authors: Brian Pulfer, Roman Chaban, Yury Belousov, Joakim Tutt, Olga Taran, Taras Holotyak, Slava Voloshynovskiy | Published: 2022-06-23 | Updated: 2022-06-25
A Framework for Understanding Model Extraction Attack and Defense
Authors: Xun Xian, Mingyi Hong, Jie Ding | Published: 2022-06-23
Multi-party Secure Broad Learning System for Privacy Preserving
Authors: Xiao-Kai Cao, Chang-Dong Wang, Jian-Huang Lai, Qiong Huang, C. L. Philip Chen | Published: 2022-06-22
A Practical Methodology for ML-Based EM Side Channel Disassemblers
Authors: Cesar N. Arguello, Hunter Searle, Sara Rampazzi, Kevin R. B. Butler | Published: 2022-06-21 | Updated: 2022-07-20
sqSGD: Locally Private and Communication Efficient Federated Learning
Authors: Yan Feng, Tao Xiong, Ruofan Wu, LingJuan Lv, Leilei Shi | Published: 2022-06-21 | Updated: 2022-06-22