Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference

24 February 2020

Papers citing "Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference"

24 / 24 papers shown

Title
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 37 2 0 26 Nov 2023
Training Image Derivatives: Increased Accuracy and Universal Robustness V. Avrutskiy 51 0 0 21 Oct 2023
Aegis: Mitigating Targeted Bit-flip Attacks against Deep Neural Networks Jialai Wang Ziyuan Zhang Meiqi Wang Han Qiu Tianwei Zhang Qi Li Zongpeng Li Tao Wei Chao Zhang AAML 27 20 0 27 Feb 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 43 18 0 29 Jan 2023
Towards Inference Efficient Deep Ensemble Learning Ziyue Li Kan Ren Yifan Yang Xinyang Jiang Yuqing Yang Dongsheng Li BDL 34 12 0 29 Jan 2023
Mind Your Heart: Stealthy Backdoor Attack on Dynamic Deep Neural Network in Edge Computing Tian Dong Ziyuan Zhang Han Qiu Tianwei Zhang Hewu Li T. Wang AAML 33 6 0 22 Dec 2022
Vision Transformer Computation and Resilience for Dynamic Inference Kavya Sreedhar Jason Clemons Rangharajan Venkatesan S. Keckler M. Horowitz 32 2 0 06 Dec 2022
Understanding the Robustness of Multi-Exit Models under Common Corruptions Akshay Mehra Skyler Seto Navdeep Jaitly B. Theobald AAML 26 3 0 03 Dec 2022
Personalized Federated Learning with Multi-branch Architecture Junki Mori T. Yoshiyama Ryo Furukawa Isamu Teranishi FedML 31 2 0 15 Nov 2022
Can pruning improve certified robustness of neural networks? Zhangheng Li Tianlong Chen Linyi Li Yue Liu Zhangyang Wang AAML 24 12 0 15 Jun 2022
A Closer Look at Branch Classifiers of Multi-exit Architectures Shaohui Lin Bo Ji Rongrong Ji Angela Yao 17 4 0 28 Apr 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses Robik Shrestha Kushal Kafle Christopher Kanan CML 38 13 0 05 Apr 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen Zhenyu Zhang Pengju Wang Santosh Balachandra Haoyu Ma Zehao Wang Zhangyang Wang OOD AAML 100 47 0 20 Feb 2022
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang Chaowei Xiao Jean Kossaifi Zhiding Yu Anima Anandkumar Zhangyang Wang 35 107 0 26 Oct 2021
Multi-Exit Vision Transformer for Dynamic Inference Arian Bakhtiarnia Qi Zhang Alexandros Iosifidis 38 26 0 29 Jun 2021
IA-RED $^2$ : Interpretability-Aware Redundancy Reduction for Vision Transformers Bowen Pan Yikang Shen Yi Ding Zhangyang Wang Rogerio Feris A. Oliva VLM ViT 44 156 0 23 Jun 2021
Graceful Degradation and Related Fields J. Dymond 36 4 0 21 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead Arian Bakhtiarnia Qi Zhang Alexandros Iosifidis 32 35 0 19 May 2021
Improving the Accuracy of Early Exits in Multi-Exit Architectures via Curriculum Learning Arian Bakhtiarnia Qi Zhang Alexandros Iosifidis 38 12 0 21 Apr 2021
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 30 228 0 26 Oct 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 18 246 0 28 Mar 2020
AdderNet: Do We Really Need Multiplications in Deep Learning? Hanting Chen Yunhe Wang Chunjing Xu Boxin Shi Chao Xu Qi Tian Chang Xu 29 194 0 31 Dec 2019
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 314 3,115 0 04 Nov 2016