Machine Learning in/for Blockchain: Future and Challenges
Authors: Fang Chen, Hong Wan, Hua Cai, Guang Cheng | Published: 2019-09-12 | Updated: 2020-12-08
Literature Database
An Empirical Investigation of Randomized Defenses against Adversarial Attacks
Authors: Yannik Potdevin, Dirk Nowotka, Vijay Ganesh | Published: 2019-09-12
Inspecting adversarial examples using the Fisher information
Authors: Jörg Martin, Clemens Elster | Published: 2019-09-12
Feedback Learning for Improving the Robustness of Neural Networks
Authors: Chang Song, Zuoguan Wang, Hai Li | Published: 2019-09-12
Learning-Guided Network Fuzzing for Testing Cyber-Physical System Defences
Authors: Yuqi Chen, Christopher M. Poskitt, Jun Sun, Sridhar Adepu, Fan Zhang | Published: 2019-09-12
Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
Authors: Luis Muñoz-González, Kenneth T. Co, Emil C. Lupu | Published: 2019-09-11
Structural Robustness for Deep Learning Architectures
Authors: Carlos Lassance, Vincent Gripon, Jian Tang, Antonio Ortega | Published: 2019-09-11
Sparse and Imperceivable Adversarial Attacks
Authors: Francesco Croce, Matthias Hein | Published: 2019-09-11
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
Identifying and Resisting Adversarial Videos Using Temporal Consistency
Authors: Xiaojun Jia, Xingxing Wei, Xiaochun Cao | Published: 2019-09-11