Verification of Neural Networks: Enhancing Scalability through Pruning

Verification of Neural Networks: Enhancing Scalability through Pruning

17 March 2020

Francesco Leofante

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Papers citing "Verification of Neural Networks: Enhancing Scalability through Pruning"

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Title
Exploiting Verified Neural Networks via Floating Point Numerical Error Kai Jia Martin Rinard AAML 71 37 0 06 Mar 2020
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 58 51 0 18 Dec 2018
Rethinking the Value of Network Pruning Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang Trevor Darrell 36 1,470 0 11 Oct 2018
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees Min Wu Matthew Wicker Wenjie Ruan Xiaowei Huang Marta Kwiatkowska AAML 53 111 0 10 Jul 2018
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 76 449 0 31 May 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,904 0 25 Aug 2017
Learning Efficient Convolutional Networks through Network Slimming Zhuang Liu Jianguo Li Zhiqiang Shen Gao Huang Shoumeng Yan Changshui Zhang 125 2,421 0 22 Aug 2017
Foolbox: A Python toolbox to benchmark the robustness of machine learning models Jonas Rauber Wieland Brendel Matthias Bethge AAML 63 283 0 13 Jul 2017
An approach to reachability analysis for feed-forward ReLU neural networks A. Lomuscio Lalit Maganti 65 359 0 22 Jun 2017
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 313 6,681 0 08 Jun 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,927 1 21 Dec 2013