activity
20182022
most citedGraph-MLP: Node Classification without Message Passing in Graph

50 citations · 63 across the 6 of their papers we have counts for

collaborators

8 papers

cs.IT2022

Joint Activity and Blind Information Detection for UAV-Assisted Massive IoT Access

Li Qiao, Jun Zhang, Zhen Gao +5

Grant-free non-coherent index-modulation (NC-IM) has been recently considered as an efficient massive access scheme for enabling cost- and energy-limited Internet-of-Things (IoT) d…

cs.LG20211 cited

Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets

Yue Gao, Kry Yik Chau Lui, Pablo Hernandez-Leal

Trading markets represent a real-world financial application to deploy reinforcement learning agents, however, they carry hard fundamental challenges such as high variance and cost…

stat.ML20211 cited

Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model

Yue Gao, Garvesh Raskutti

Network estimation from multi-variate point process or time series data is a problem of fundamental importance. Prior work has focused on parametric approaches that require a known…

cs.CV20218 cited

Relation Modeling in Spatio-Temporal Action Localization

Yutong Feng, Jianwen Jiang, Ziyuan Huang +5

This paper presents our solution to the AVA-Kinetics Crossover Challenge of ActivityNet workshop at CVPR 2021. Our solution utilizes multiple types of relation modeling methods for…

cs.LG202150 cited

Graph-MLP: Node Classification without Message Passing in Graph

Yang Hu, Haoxuan You, Zhecan Wang +3

Graph Neural Network (GNN) has been demonstrated its effectiveness in dealing with non-Euclidean structural data. Both spatial-based and spectral-based GNNs are relying on adjacenc…

cs.CV2020

3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection

He Wang, Yezhen Cong, Or Litany +2

3D object detection is an important yet demanding task that heavily relies on difficult to obtain 3D annotations. To reduce the required amount of supervision, we propose 3DIoUMatc…