Robust Machine Learning via Privacy/Rate-Distortion Theory

Robust Machine Learning via Privacy/Rate-Distortion Theory

22 July 2020

Adnan Siraj Rakin

Papers citing "Robust Machine Learning via Privacy/Rate-Distortion Theory"

8 / 8 papers shown

Title
Probabilistic Safety Regions Via Finite Families of Scalable Classifiers Alberto Carlevaro Teodoro Alamo Fabrizio Dabbene Maurizio Mongelli 34 2 0 08 Sep 2023
Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems Jirong Yi Q. Zhang Zhengbo Chen Qiaoan Liu Weizhuo Shao Yusen He Yao Wang SSL 28 0 0 23 Nov 2022
Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems Jirong Yi Q. Zhang Zhenji Chen Qiaoan Liu Weizhuo Shao SSL FedML 31 3 0 21 Sep 2022
Generative Adversarial User Privacy in Lossy Single-Server Information Retrieval Chung-Wei Weng Yauhen Yakimenka Hsuan-Yin Lin E. Rosnes Joerg Kliewer 35 3 0 07 Dec 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,838 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,842 0 08 Jul 2016
Privacy Against Statistical Inference Flavio du Pin Calmon N. Fawaz FedML 100 345 0 08 Oct 2012