Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness

15 June 2022

Papers citing "Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness"

23 / 23 papers shown

Title
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu Qixuan Yu Yang Zhang Shan-Hung Wu Ouyang Xu David D. Cox Yingyan Lin AAML OOD 77 30 0 26 Oct 2021
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results Stanley Bak Changliu Liu Taylor T. Johnson NAI 75 112 0 31 Aug 2021
On the Effect of Pruning on Adversarial Robustness Artur Jordão Hélio Pedrini AAML 68 22 0 10 Aug 2021
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers Kaidi Xu Huan Zhang Shiqi Wang Yihan Wang Suman Jana Xue Lin Cho-Jui Hsieh 82 183 0 27 Nov 2020
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming Sumanth Dathathri Krishnamurthy Dvijotham Alexey Kurakin Aditi Raghunathan J. Uesato ... Shreya Shankar Jacob Steinhardt Ian Goodfellow Percy Liang Pushmeet Kohli AAML 97 95 0 22 Oct 2020
Lagrangian Decomposition for Neural Network Verification Rudy Bunel Alessandro De Palma Alban Desmaison Krishnamurthy Dvijotham Pushmeet Kohli Philip Torr M. P. Kumar 50 50 0 24 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 138 1,177 0 12 Jan 2020
Importance Estimation for Neural Network Pruning Pavlo Molchanov Arun Mallya Stephen Tyree I. Frosio Jan Kautz 3DPC 78 881 0 25 Jun 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 67 347 0 14 Jun 2019
Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui Haotao Wang Chen Yu Haichuan Yang Zhangyang Wang Ji Liu MQ 47 138 0 10 Feb 2019
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 76 448 0 31 May 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 73 547 0 05 Mar 2018
SkipNet: Learning Dynamic Routing in Convolutional Networks Xin Wang Feng Yu Zi-Yi Dou Trevor Darrell Joseph E. Gonzalez 101 636 0 26 Nov 2017
BlockDrop: Dynamic Inference Paths in Residual Networks Zuxuan Wu Tushar Nagarajan Abhishek Kumar Steven J. Rennie L. Davis Kristen Grauman Rogerio Feris 87 466 0 22 Nov 2017
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 191 1,276 0 05 Oct 2017
Learning Efficient Convolutional Networks through Network Slimming Zhuang Liu Jianguo Li Zhiqiang Shen Gao Huang Shoumeng Yan Changshui Zhang 122 2,420 0 22 Aug 2017
Channel Pruning for Accelerating Very Deep Neural Networks Yihui He Xiangyu Zhang Jian Sun 199 2,524 0 19 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,063 0 19 Jun 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 315 1,867 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 215 943 0 21 Oct 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 253 8,833 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 310 6,672 0 08 Jun 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 268 14,918 1 21 Dec 2013