Adversarial Attacks on Gaussian Process Bandits
Authors: Eric Han, Jonathan Scarlett | Published: 2021-10-16 | Updated: 2022-06-16
Algorithm Design
Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis
Authors: Yi Liu, Yuanshao Zhu, James J. Q. Yu | Published: 2021-10-14
Combining Differential Privacy and Byzantine Resilience in Distributed SGD
Authors: Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sebastien Rouault, John Stephan | Published: 2021-10-08 | Updated: 2023-10-05
Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning
Authors: Anis Elgabli, Jihong Park, Chaouki Ben Issaid, Mehdi Bennis | Published: 2020-07-03 | Updated: 2020-11-17
Trace-Norm Adversarial Examples
Authors: Ehsan Kazemi, Thomas Kerdreux, Liqiang Wang | Published: 2020-07-02
Multi-Task Variational Information Bottleneck
Authors: Weizhu Qian, Bowei Chen, Yichao Zhang, Guanghui Wen, Franck Gechter | Published: 2020-07-01 | Updated: 2021-03-01
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
Authors: Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong | Published: 2020-06-27 | Updated: 2021-03-18
Deep Partition Aggregation: Provable Defense against General Poisoning Attacks
Authors: Alexander Levine, Soheil Feizi | Published: 2020-06-26 | Updated: 2021-03-18
From Predictions to Decisions: Using Lookahead Regularization
Authors: Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes | Published: 2020-06-20 | Updated: 2020-06-23
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
Authors: Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang | Published: 2020-06-20 | Updated: 2020-06-23