19 citations · 82 across the 31 of their papers we have counts for
6 papers · 1 filter
User-Oriented Robust Reinforcement Learning
Haoyi You, Beichen Yu, Haiming Jin +2
Recently, improving the robustness of policies across different environments attracts increasing attention in the reinforcement learning (RL) community. Existing robust RL methods…
DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning
Zhaoxing Yang, Rong Ding, Haiming Jin +5
In recent years, multi-agent reinforcement learning (MARL) has presented impressive performance in various applications. However, physical limitations, budget restrictions, and man…
Networked Time Series Prediction with Incomplete Data via Generative Adversarial Network
Yichen Zhu, Bo Jiang, Haiming Jin +5
A networked time series (NETS) is a family of time series on a given graph, one for each node. It has a wide range of applications from intelligent transportation, environment moni…
Privacy Threats Analysis to Secure Federated Learning
Yuchen Li, Yifan Bao, Liyao Xiang +4
Federated learning is emerging as a machine learning technique that trains a model across multiple decentralized parties. It is renowned for preserving privacy as the data never le…
Certified Distributional Robustness on Smoothed Classifiers
Jungang Yang, Liyao Xiang, Ruidong Chen +3
The robustness of deep neural networks (DNNs) against adversarial example attacks has raised wide attention. For smoothed classifiers, we propose the worst-case adversarial loss ov…
On Geometric Structure of Activation Spaces in Neural Networks
Yuting Jia, Haiwen Wang, Shuo Shao +3
In this paper, we investigate the geometric structure of activation spaces of fully connected layers in neural networks and then show applications of this study. We propose an effi…