mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks
Authors: Hai Shu, Ronghua Shi, Qiran Jia, Hongtu Zhu, Ziqi Chen | Published: 2020-06-05 | Updated: 2022-05-08
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Towards Understanding Fast Adversarial Training
Authors: Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin | Published: 2020-06-04
Characterizing the Weight Space for Different Learning Models
Authors: Saurav Musunuru, Jay N. Paranjape, Rahul Kumar Dubey, Vijendran G. Venkoparao | Published: 2020-06-04
Detecting Audio Attacks on ASR Systems with Dropout Uncertainty
Authors: Tejas Jayashankar, Jonathan Le Roux, Pierre Moulin | Published: 2020-06-02 | Updated: 2020-09-15
SearchFromFree: Adversarial Measurements for Machine Learning-based Energy Theft Detection
Authors: Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun | Published: 2020-06-02 | Updated: 2020-08-30
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization
Authors: Mayumi Ohta, Nathaniel Berger, Artem Sokolov, Stefan Riezler | Published: 2020-06-02 | Updated: 2020-06-29
Perturbation Analysis of Gradient-based Adversarial Attacks
Authors: Utku Ozbulak, Manvel Gasparyan, Wesley De Neve, Arnout Van Messem | Published: 2020-06-02
Exploring the role of Input and Output Layers of a Deep Neural Network in Adversarial Defense
Authors: Jay N. Paranjape, Rahul Kumar Dubey, Vijendran V Gopalan | Published: 2020-06-02
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods
Authors: Kyungmi Lee, Anantha P. Chandrakasan | Published: 2020-06-01
DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks
Authors: Hanieh Hashemi, Yongqin Wang, Murali Annavaram | Published: 2020-06-01 | Updated: 2020-10-15