ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness
Authors: Anindya Sarkar, Anirudh Sunder Raj, Raghu Sesha Iyengar | Published: 2019-10-15 | Updated: 2020-09-27
モデルの堅牢性
They Might NOT Be Giants: Crafting Black-Box Adversarial Examples with Fewer Queries Using Particle Swarm Optimization
Authors: Rayan Mosli, Matthew Wright, Bo Yuan, Yin Pan | Published: 2019-09-16
PDA: Progressive Data Augmentation for General Robustness of Deep Neural Networks
Authors: Hang Yu, Aishan Liu, Xianglong Liu, Gengchao Li, Ping Luo, Ran Cheng, Jichen Yang, Chongzhi Zhang | Published: 2019-09-11 | Updated: 2020-02-24
Defending Against Adversarial Attacks by Leveraging an Entire GAN
Authors: Gokula Krishnan Santhanam, Paulina Grnarova | Published: 2018-05-27
Cautious Deep Learning
Authors: Yotam Hechtlinger, Barnabás Póczos, Larry Wasserman | Published: 2018-05-24 | Updated: 2019-02-27
Towards Robust Training of Neural Networks by Regularizing Adversarial Gradients
Authors: Fuxun Yu, Zirui Xu, Yanzhi Wang, Chenchen Liu, Xiang Chen | Published: 2018-05-23 | Updated: 2018-06-07
Adversarially Robust Training through Structured Gradient Regularization
Authors: Kevin Roth, Aurelien Lucchi, Sebastian Nowozin, Thomas Hofmann | Published: 2018-05-22
Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks
Authors: Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha | Published: 2018-05-20 | Updated: 2019-10-03
Curriculum Adversarial Training
Authors: Qi-Zhi Cai, Min Du, Chang Liu, Dawn Song | Published: 2018-05-13
Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression
Authors: Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng Chau | Published: 2017-05-08