8 citations · 18 across the 9 of their papers we have counts for
4 papers · 1 filter
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning
Puning Zhao, Fei Yu, Zhiguo Wan
Federated learning systems are susceptible to adversarial attacks. To combat this, we introduce a novel aggregator based on Huber loss minimization, and provide a comprehensive the…
Minimax Optimal Q Learning with Nearest Neighbors
Puning Zhao, Lifeng Lai
Analyzing the Markov decision process (MDP) with continuous state spaces is generally challenging. A recent interesting work \cite{shah2018q} solves MDP with bounded continuous sta…
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers
Wenyu Liu, Tianqiang Huang, Pengfei Zhang +3
Adversarial attacks pose a major challenge to distributed learning systems, prompting the development of numerous robust learning methods. However, most existing approaches suffer…
Robust Nonparametric Regression under Poisoning Attack
Puning Zhao, Zhiguo Wan
This paper studies robust nonparametric regression, in which an adversarial attacker can modify the values of up to samples from a training dataset of size . Our initial sol…