Improving Adversarial Robustness of Ensembles with Diversity Training

28 January 2019

Papers citing "Improving Adversarial Robustness of Ensembles with Diversity Training"

20 / 20 papers shown

Title
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models Yoojin Jung Byung Cheol Song AAML VLM MQ 36 0 0 07 Apr 2025
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications Siyuan Mu Sen Lin MoE 129 1 0 10 Mar 2025
Survey of Computerized Adaptive Testing: A Machine Learning Perspective Qi Liu Zhuang Yan Haoyang Bi Zhenya Huang Weizhe Huang ... Z. Pardos Haiping Ma Mengxiao Zhu Shijin Wang Enhong Chen AI4Ed 38 9 0 31 Mar 2024
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications Hangsheng Zhang Jiqiang Liu Jinsong Dong AAML 21 1 0 20 Jan 2024
Semantic and Expressive Variation in Image Captions Across Languages Andre Ye Sebastin Santy Jena D. Hwang Amy X. Zhang Ranjay Krishna VLM 50 3 0 22 Oct 2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness Ruoxi Qin Linyuan Wang Xuehui Du Xing-yuan Chen Binghai Yan AAML 26 0 0 01 Aug 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations Hassan Dbouk Naresh R Shanbhag AAML 23 7 0 02 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles Taiga Abe E. Kelly Buchanan Geoff Pleiss John P. Cunningham UQCV 38 13 0 01 Feb 2023
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 40 15 0 07 Jun 2022
3D Common Corruptions and Data Augmentation Oğuzhan Fatih Kar Teresa Yeo Andrei Atanov Amir Zamir 3DPC 35 107 0 02 Mar 2022
Mitigating Adversarial Attacks by Distributing Different Copies to Different Users Jiyi Zhang Hansheng Fang W. Tann Ke Xu Chengfang Fang E. Chang AAML 21 3 0 30 Nov 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 13 48 0 22 Jul 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey A. Hengel 23 86 0 12 May 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness Yi Cai Xuefei Ning Huazhong Yang Yu Wang AAML 25 4 0 27 Mar 2021
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 19 11 0 21 Sep 2020
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability Kaizhao Liang Jacky Y. Zhang Boxin Wang Zhuolin Yang Oluwasanmi Koyejo B. Li AAML 23 25 0 25 Jun 2020
Deep Neural Network Perception Models and Robust Autonomous Driving Systems M. Shafiee Ahmadreza Jeddi Amir Nazemi Paul Fieguth A. Wong OOD 14 14 0 04 Mar 2020
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 25 9 0 31 Oct 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 22 18 0 27 Sep 2019
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016