Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework
Authors: Pranay Sharma, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Xue Lin, Pramod K. Varshney | Published: 2020-12-21
Optimization Methods
Ditto: Fair and Robust Federated Learning Through Personalization
Authors: Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith | Published: 2020-12-08 | Updated: 2021-06-15
SSGD: A safe and efficient method of gradient descent
Authors: Jinhuan Duan, Xianxian Li, Shiqi Gao, Jinyan Wang, Zili Zhong | Published: 2020-12-03 | Updated: 2021-04-26
Towards Understanding the Dynamics of the First-Order Adversaries
Authors: Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su | Published: 2020-10-20
Tight Second-Order Certificates for Randomized Smoothing
Authors: Alexander Levine, Aounon Kumar, Thomas Goldstein, Soheil Feizi | Published: 2020-10-20 | Updated: 2020-12-15
Privacy-preserving Data Sharing on Vertically Partitioned Data
Authors: Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela | Published: 2020-10-19 | Updated: 2022-09-02
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization
Authors: Pranav Subramani, Nicholas Vadivelu, Gautam Kamath | Published: 2020-10-18 | Updated: 2021-10-26
Bag of Tricks for Adversarial Training
Authors: Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu | Published: 2020-10-01 | Updated: 2021-03-31
StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks
Authors: Guangmo Tong | Published: 2020-09-29
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations
Authors: Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu | Published: 2020-09-29 | Updated: 2022-08-17