Sparse DNNs with Improved Adversarial Robustness

23 October 2018

Papers citing "Sparse DNNs with Improved Adversarial Robustness"

25 / 25 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
Navigating Extremes: Dynamic Sparsity in Large Output Spaces Nasib Ullah Erik Schultheis Mike Lasby Yani Andrew Ioannou Rohit Babbar 35 0 0 05 Nov 2024
Specification Overfitting in Artificial Intelligence Benjamin Roth Pedro Henrique Luz de Araujo Yuxi Xia Saskia Kaltenbrunner Christoph Korab 58 0 0 13 Mar 2024
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! Shiwei Liu Tianlong Chen Zhenyu (Allen) Zhang Xuxi Chen Tianjin Huang Ajay Jaiswal Zhangyang Wang 29 29 0 03 Mar 2023
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 11 2 0 04 Nov 2022
Biological connectomes as a representation for the architecture of artificial neural networks Samuel Schmidgall Catherine D. Schuman Maryam Parsa 18 2 0 28 Sep 2022
EPIC TTS Models: Empirical Pruning Investigations Characterizing Text-To-Speech Models Perry Lam Huayun Zhang Nancy F. Chen Berrak Sisman 11 2 0 22 Sep 2022
Towards Sparsification of Graph Neural Networks Hongwu Peng Deniz Gurevin Shaoyi Huang Tong Geng Weiwen Jiang O. Khan Caiwen Ding GNN 30 24 0 11 Sep 2022
On the Robustness and Anomaly Detection of Sparse Neural Networks Morgane Ayle Bertrand Charpentier John Rachwan Daniel Zügner Simon Geisler Stephan Günnemann AAML 52 3 0 09 Jul 2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts Haotao Wang Junyuan Hong Jiayu Zhou Zhangyang Wang OOD 56 11 0 04 Jul 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 19 2 0 08 Jun 2022
Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning Julian Burghoff Robin Shing Moon Chan Hanno Gottschalk Annika Muetze Tobias Riedlinger Matthias Rottmann Marius Schubert BDL 23 0 0 30 May 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 39 38 0 26 May 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen Zhenyu (Allen) Zhang Pengju Wang Santosh Balachandra Haoyu Ma Zehao Wang Zhangyang Wang OOD AAML 77 46 0 20 Feb 2022
Finding Dynamics Preserving Adversarial Winning Tickets Xupeng Shi Pengfei Zheng Adam Ding Yuan Gao Weizhong Zhang AAML 21 1 0 14 Feb 2022
Deadwooding: Robust Global Pruning for Deep Neural Networks Sawinder Kaur Ferdinando Fioretto Asif Salekin 19 4 0 10 Feb 2022
Learning Robust and Lightweight Model through Separable Structured Transformations Xian Wei Yanhui Huang Yang Xu Mingsong Chen Hai Lan Yuanxiang Li Zhongfeng Wang Xuan Tang OOD 24 0 0 27 Dec 2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy Lucas Liebenwein Cenk Baykal Brandon Carter David K Gifford Daniela Rus AAML 32 71 0 04 Mar 2021
Robustness and Transferability of Universal Attacks on Compressed Models Alberto G. Matachana Kenneth T. Co Luis Muñoz-González David Martínez Emil C. Lupu AAML 26 10 0 10 Dec 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 46 8 0 03 Nov 2020
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks Abhiroop Bhattacharjee Priyadarshini Panda AAML 20 19 0 25 Aug 2020
Yet Another Intermediate-Level Attack Qizhang Li Yiwen Guo Hao Chen AAML 24 51 0 20 Aug 2020
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild Rahul Duggal Scott Freitas Cao Xiao Duen Horng Chau Jimeng Sun 28 22 0 29 Jan 2020
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 32 21 0 30 May 2019
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations Subutai Ahmad Luiz Scheinkman 25 96 0 27 Mar 2019