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Attacking Binarized Neural Networks

1 November 2017

Papers citing "Attacking Binarized Neural Networks"

50 / 59 papers shown

Title
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization Jianting Yang Srecko Ðurasinovic Jean B. Lasserre Victor Magron Jun Zhao AAML 139 1 0 27 May 2024
QGen: On the Ability to Generalize in Quantization Aware Training Mohammadhossein Askarihemmat Ahmadreza Jeddi Reyhane Askari Hemmat Ivan Lazarevich Alexander Hoffman Sudhakar Sah Ehsan Saboori Yvon Savaria Jean-Pierre David MQ 99 1 0 17 Apr 2024
Investigating the Impact of Quantization on Adversarial Robustness Qun Li Yuan Meng Chen Tang Jiacheng Jiang Zhi Wang 79 5 0 08 Apr 2024
The Impact of Quantization on the Robustness of Transformer-based Text Classifiers Seyed Parsa Neshaei Yasaman Boreshban Gholamreza Ghassem-Sani Seyed Abolghasem Mirroshandel MQ 58 0 0 08 Mar 2024
ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks Peng Zhao Jiehua Zhang Bowen Peng Longguang Wang Yingmei Wei Yu Liu Li Liu AAML 86 0 0 21 Dec 2023
Relationship between Model Compression and Adversarial Robustness: A Review of Current Evidence Svetlana Pavlitska Hannes Grolig J. Marius Zöllner AAML 138 3 0 27 Nov 2023
BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs Jou-An Chen Hsin-Hsuan Sung Xipeng Shen Sutanay Choudhury Ang Li GNN MQ 82 7 0 04 May 2023
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks Ferheen Ayaz Idris Zakariyya José Cano S. Keoh Jeremy Singer D. Pau Mounia Kharbouche-Harrari 60 6 0 25 Apr 2023
Adversarial Attacks on Machine Learning in Embedded and IoT Platforms Christian Westbrook S. Pasricha AAML 71 3 0 03 Mar 2023
Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition Juan Carrasquilla Mohamed Hibat-Allah E. Inack Alireza Makhzani Kirill Neklyudov Graham Taylor G. Torlai MQ 65 9 0 19 Jan 2023
Understanding Real-world Threats to Deep Learning Models in Android Apps Zizhuang Deng Kai Chen Guozhu Meng Xiaodong Zhang Ke Xu Yao Cheng AAML 70 29 0 20 Sep 2022
Hardening DNNs against Transfer Attacks during Network Compression using Greedy Adversarial Pruning Jonah O'Brien Weiss Tiago A. O. Alves S. Kundu AAML 28 0 0 15 Jun 2022
GAAF: Searching Activation Functions for Binary Neural Networks through Genetic Algorithm Yanfei Li Tong Geng S. Stein Ang Li Hui-Ling Yu MQ 80 8 0 05 Jun 2022
Hardware Approximate Techniques for Deep Neural Network Accelerators: A Survey Giorgos Armeniakos Georgios Zervakis Dimitrios Soudris J. Henkel 284 98 0 16 Mar 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 87 4 0 03 Feb 2022
Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edge Deepsayan Sadhukhan N. Shankar Nancy Nayak¢Ó Thulasi Tholeti¢Ô Sheetal Kalyani¢Ó MQ 21 4 0 27 Oct 2021
Defensive Tensorization Adrian Bulat Jean Kossaifi S. Bhattacharya Yannis Panagakis Timothy M. Hospedales Georgios Tzimiropoulos Nicholas D. Lane Maja Pantic AAML 32 4 0 26 Oct 2021
A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness Chang Song Riya Ranjan H. Li MQ 67 4 0 23 Oct 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency Yonggan Fu Yang Zhao Qixuan Yu Chaojian Li Yingyan Lin AAML 170 14 0 11 Sep 2021
Tensor Normalization and Full Distribution Training Wolfgang Fuhl OOD 96 4 0 06 Sep 2021
Gradient-Based Interpretability Methods and Binarized Neural Networks Amy Widdicombe S. Julier FAtt 54 1 0 23 Jun 2021
Enhancing Robustness of Neural Networks through Fourier Stabilization Netanel Raviv Aidan Kelley Michael M. Guo Yevgeny Vorobeychik AAML 29 13 0 08 Jun 2021
On the Adversarial Robustness of Quantized Neural Networks Micah Gorsline James T. Smith Cory E. Merkel AAML 93 19 0 01 May 2021
BCNN: Binary Complex Neural Network Yanfei Li Tong Geng Ang Li Huimin Yu MQ 51 8 0 28 Mar 2021
Recent Advances in Large Margin Learning Yiwen Guo Changshui Zhang AAML AI4CE 121 13 0 25 Mar 2021
BreakingBED -- Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks M. Vemparala Alexander Frickenstein Nael Fasfous Lukas Frickenstein Qi Zhao ... Daniel Ehrhardt Yuankai Wu C. Unger N. S. Nagaraja W. Stechele AAML 33 7 0 14 Mar 2021
Improving Adversarial Robustness in Weight-quantized Neural Networks Chang Song Elias Fallon Hai Helen Li AAML 61 19 0 29 Dec 2020
Towards the Quantification of Safety Risks in Deep Neural Networks Peipei Xu Wenjie Ruan Xiaowei Huang 47 7 0 13 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 136 164 0 08 Sep 2020
Defending against substitute model black box adversarial attacks with the 01 loss Yunzhe Xue Meiyan Xie Usman Roshan AAML 34 1 0 01 Sep 2020
Towards adversarial robustness with 01 loss neural networks Yunzhe Xue Meiyan Xie Usman Roshan OOD AAML 66 5 0 20 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 118 73 0 07 Aug 2020
Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs Ang Li Simon Su MQ 85 35 0 30 Jun 2020
On the transferability of adversarial examples between convex and 01 loss models Yunzhe Xue Meiyan Xie Usman Roshan AAML 29 7 0 14 Jun 2020
Understanding Learning Dynamics of Binary Neural Networks via Information Bottleneck Vishnu Raj Nancy Nayak Sheetal Kalyani MQ 70 5 0 13 Jun 2020
DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks H. Hashemi Yongqin Wang M. Annavaram FedML 84 26 0 01 Jun 2020
Quantized Neural Networks: Characterization and Holistic Optimization Yoonho Boo Sungho Shin Wonyong Sung MQ 78 8 0 31 May 2020
Efficient Exact Verification of Binarized Neural Networks Kai Jia Martin Rinard AAML MQ 48 59 0 07 May 2020
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks Sanchari Sen Balaraman Ravindran A. Raghunathan FedML AAML 63 63 0 21 Apr 2020
Improved Gradient based Adversarial Attacks for Quantized Networks Kartik Gupta Thalaiyasingam Ajanthan MQ 58 19 0 30 Mar 2020
Robust binary classification with the 01 loss Yunzhe Xue Meiyan Xie Usman Roshan OOD 24 1 0 09 Feb 2020
Exploring Adversarial Attack in Spiking Neural Networks with Spike-Compatible Gradient Ling Liang Xing Hu Lei Deng Yujie Wu Guoqi Li Yufei Ding Peng Li Yuan Xie AAML 122 63 0 01 Jan 2020
Exploring the Back Alleys: Analysing The Robustness of Alternative Neural Network Architectures against Adversarial Attacks Y. Tan Yuval Elovici Alexander Binder AAML 84 3 0 08 Dec 2019
Error-Correcting Output Codes with Ensemble Diversity for Robust Learning in Neural Networks Yang Song Qiyu Kang Wee Peng Tay AAML 75 21 0 30 Nov 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 98 18 0 27 Sep 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 89 105 0 25 Jun 2019
Defensive Quantization: When Efficiency Meets Robustness Ji Lin Chuang Gan Song Han MQ 118 204 0 17 Apr 2019
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks Priyadarshini Panda I. Chakraborty Kaushik Roy AAML 62 40 0 08 Feb 2019
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing Jingyi Wang Guoliang Dong Jun Sun Xinyu Wang Peixin Zhang AAML 80 191 0 14 Dec 2018
Sparse DNNs with Improved Adversarial Robustness Yiwen Guo Chao Zhang Changshui Zhang Yurong Chen AAML 100 154 0 23 Oct 2018