Federated Learning with Matched Averaging
Authors: Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris Papailiopoulos, Yasaman Khazaeni | Published: 2020-02-15
深層学習手法
Fast is better than free: Revisiting adversarial training
Authors: Eric Wong, Leslie Rice, J. Zico Kolter | Published: 2020-01-12
Campfire: Compressible, Regularization-Free, Structured Sparse Training for Hardware Accelerators
Authors: Noah Gamboa, Kais Kudrolli, Anand Dhoot, Ardavan Pedram | Published: 2020-01-09 | Updated: 2020-01-13
Learning to Prevent Leakage: Privacy-Preserving Inference in the Mobile Cloud
Authors: Shuang Zhang, Liyao Xiang, Congcong Li, Yixuan Wang, Quanshi Zhang, Wei Wang, Bo Li | Published: 2019-12-18 | Updated: 2021-06-15
DAmageNet: A Universal Adversarial Dataset
Authors: Sizhe Chen, Xiaolin Huang, Zhengbao He, Chengjin Sun | Published: 2019-12-16
Potential adversarial samples for white-box attacks
Authors: Amir Nazemi, Paul Fieguth | Published: 2019-12-13
Detecting and Correcting Adversarial Images Using Image Processing Operations
Authors: Huy H. Nguyen, Minoru Kuribayashi, Junichi Yamagishi, Isao Echizen | Published: 2019-12-11 | Updated: 2019-12-30
Training Provably Robust Models by Polyhedral Envelope Regularization
Authors: Chen Liu, Mathieu Salzmann, Sabine Süsstrunk | Published: 2019-12-10 | Updated: 2021-09-20
Stealing Knowledge from Protected Deep Neural Networks Using Composite Unlabeled Data
Authors: Itay Mosafi, Eli David, Nathan S. Netanyahu | Published: 2019-12-09
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness
Authors: Adam Noack, Isaac Ahern, Dejing Dou, Boyang Li | Published: 2019-12-07 | Updated: 2020-12-04