LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity
Authors: Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen | Published: 2022-07-26
Generative Extraction of Audio Classifiers for Speaker Identification
Authors: Tejumade Afonja, Lucas Bourtoule, Varun Chandrasekaran, Sageev Oore, Nicolas Papernot | Published: 2022-07-26
$p$-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations
Authors: Adam Dziedzic, Stephan Rabanser, Mohammad Yaghini, Armin Ale, Murat A. Erdogdu, Nicolas Papernot | Published: 2022-07-25
Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning
Authors: Xinlei He, Hongbin Liu, Neil Zhenqiang Gong, Yang Zhang | Published: 2022-07-25
SecretGen: Privacy Recovery on Pre-Trained Models via Distribution Discrimination
Authors: Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao, Bo Li | Published: 2022-07-25
Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence
Authors: Markus Bayer, Tobias Frey, Christian Reuter | Published: 2022-07-22
Applying Machine Learning on RSRP-based Features for False Base Station Detection
Authors: Prajwol Kumar Nakarmi, Jakob Sternby, Ikram Ullah | Published: 2022-07-22
Privacy and Transparency in Graph Machine Learning: A Unified Perspective
Authors: Megha Khosla | Published: 2022-07-22 | Updated: 2022-10-19
Careful What You Wish For: on the Extraction of Adversarially Trained Models
Authors: Kacem Khaled, Gabriela Nicolescu, Felipe Gohring de Magalhães | Published: 2022-07-21
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
Authors: Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Kentaro Ohno, Yasutoshi Ida | Published: 2022-07-21 | Updated: 2023-04-26