activity
20182023
most citedLearning to Communicate and Correct Pose Errors

9 citations · 18 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2021

Cost-Efficient Online Hyperparameter Optimization

Jingkang Wang, Mengye Ren, Ilija Bogunovic +2

Recent work on hyperparameters optimization (HPO) has shown the possibility of training certain hyperparameters together with regular parameters. However, these online HPO algorith…

cs.LG2021

Adversarial Attacks On Multi-Agent Communication

James Tu, Tsunhsuan Wang, Jingkang Wang +3

Growing at a fast pace, modern autonomous systems will soon be deployed at scale, opening up the possibility for cooperative multi-agent systems. Sharing information and distributi…

cs.CV20209 cited

Learning to Communicate and Correct Pose Errors

Nicholas Vadivelu, Mengye Ren, James Tu +2

Learned communication makes multi-agent systems more effective by aggregating distributed information. However, it also exposes individual agents to the threat of erroneous message…

cs.LG2020

Policy Learning Using Weak Supervision

Jingkang Wang, Hongyi Guo, Zhaowei Zhu +1

Most existing policy learning solutions require the learning agents to receive high-quality supervision signals such as well-designed rewards in reinforcement learning (RL) or high…

cs.LG2018

One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy

Jingkang Wang, Ruoxi Jia, Gerald Friedland +2

Despite the great success achieved in machine learning (ML), adversarial examples have caused concerns with regards to its trustworthiness: A small perturbation of an input results…

cs.LG2018

Reinforcement Learning with Perturbed Rewards

Jingkang Wang, Yang Liu, Bo Li

Recent studies have shown that reinforcement learning (RL) models are vulnerable in various noisy scenarios. For instance, the observed reward channel is often subject to noise in…