Game Theoretic Mixed Experts for Combinational Adversarial Machine
Learning

Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning

26 November 2022

Ethan Rathbun

Caiwen Ding

Marten van Dijk

Papers citing "Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning"

5 / 5 papers shown

Title
Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness Jieren Deng Hanbin Hong A. Palmer Xin Zhou Jinbo Bi Kaleel Mahmood Yuan Hong Derek Aguiar AAML 33 0 0 25 May 2024
The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers Orson Mengara AAML 41 3 0 03 Jan 2024
PubDef: Defending Against Transfer Attacks From Public Models Chawin Sitawarin Jaewon Chang David Huang Wesson Altoyan David A. Wagner AAML 21 5 0 26 Oct 2023
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games Maria-Florina Balcan Rattana Pukdee Pradeep Ravikumar Hongyang R. Zhang AAML 28 13 0 23 Oct 2022
Deep Residual Learning in Spiking Neural Networks Wei Fang Zhaofei Yu Yanqing Chen Tiejun Huang T. Masquelier Yonghong Tian 121 474 0 08 Feb 2021