Hongkuan Zhou

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 43

Top Topics

Kernel Density Estimation

Imitation Learning

Neural Network Training

Graph Representation

Top Venues

Proc. VLDB Endow.

IEEE Signal Process. Lett.

Publications

Hao Wang, Ruonan Liu, Steven X. Ding, Qinghua Hu, Zengxiang Li, Hongkuan Zhou
Causal-Trivial Attention Graph Neural Network for Fault Diagnosis of Complex Industrial Processes. IEEE Trans. Ind. Informatics 20 (2) (2024)
Gangda Deng, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor K. Prasanna
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. IPDPS (2024)
Gangda Deng, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor K. Prasanna
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. CoRR (2024)
Jiasheng Zhang, Di Hu, Tao Yang, Hongkuan Zhou, Xianling Li
A time series and deep fusion framework for rotating machinery fault diagnosis. Eng. Appl. Artif. Intell. 128 (2024)
Hongkuan Zhou, Xiangtong Yao, Yuan Meng, Siming Sun, Zhenshan Bing, Kai Huang, Alois Knoll
Language-conditioned Learning for Robotic Manipulation: A Survey. CoRR (2023)
Hongkuan Zhou, Aifen Sui, Wei Cao, Letian Shi
What Matters to Enhance Traffic Rule Compliance of Imitation Learning for Automated Driving. CoRR (2023)
Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. INFOCOM (2023)
Zhenshan Bing, Hongkuan Zhou, Rui Li, Xiaojie Su, Fabrice O. Morin, Kai Huang, Alois C. Knoll
Solving Robotic Manipulation With Sparse Reward Reinforcement Learning Via Graph-Based Diversity and Proximity. IEEE Trans. Ind. Electron. 70 (3) (2023)
Xiangtong Yao, Zhenshan Bing, Genghang Zhuang, Kejia Chen, Hongkuan Zhou, Kai Huang, Alois Knoll
Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions. IROS (2023)
Hongkuan Zhou, Zhenshan Bing, Xiangtong Yao, Xiaojie Su, Chenguang Yang, Kai Huang, Alois C. Knoll
Language-Conditioned Imitation Learning with Base Skill Priors under Unstructured Data. CoRR (2023)
Hongkuan Zhou, Aifen Sui, Letian Shi, Yinxian Li
Penalty-Based Imitation Learning With Cross Semantics Generation Sensor Fusion for Autonomous Driving. ITSC (2023)
Gangda Deng, Ömer Faruk Akgül, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Jianbo Li, Viktor K. Prasanna
An Efficient Distributed Graph Engine for Deep Learning on Graphs. SC Workshops (2023)
Hongkuan Zhou, Aifen Sui, Letian Shi
Penalty-Based Imitation Learning With Cross Semantics Generation Sensor Fusion for Autonomous Driving. CoRR (2023)
Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. CoRR (2023)
Jiaxi Cui, Pei Liu, Kehao Wang, Hongkuan Zhou, Yue Zhang, Xinghua Sun, Stefano Buzzi
Spectral Efficiency Analysis of Downlink Transmission for Two-Way Cell-Free Massive MIMO System With Few-Bit ADCs. PIMRC (2023)
Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. SC (2023)
Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. CoRR (2023)
Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs. CoRR (2022)
Hongkuan Zhou, Da Zheng, Israt Nisa, Vassilis N. Ioannidis, Xiang Song, George Karypis
TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs. Proc. VLDB Endow. 15 (8) (2022)
Hongkuan Zhou, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA. IPDPS (2022)
Ta-Yang Wang, Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna
Throughput optimization in heterogeneous MIMO networks: a GNN-based approach. GNNet@CoNEXT (2022)
Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. CoRR (2022)
Xiangtong Yao, Zhenshan Bing, Genghang Zhuang, Kejia Chen, Hongkuan Zhou, Kai Huang, Alois C. Knoll
Learning from Symmetry: Meta-Reinforcement Learning with Symmetric Data and Language Instructions. CoRR (2022)
Hongkuan Zhou, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA. CoRR (2022)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, efficient and scalable training of Graph Neural Networks. J. Parallel Distributed Comput. 147 (2021)
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. Proc. VLDB Endow. 14 (9) (2021)
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. CoRR (2021)
Yuxuan Zhou, Yining Dong, Hongkuan Zhou, Gang Tang
Deep Dynamic Adaptive Transfer Network for Rolling Bearing Fault Diagnosis With Considering Cross-Machine Instance. IEEE Trans. Instrum. Meas. 70 (2021)
Jiangwei Xu, Kehao Wang, Xun Zhang, Pei Liu, Dejin Kong, Hongkuan Zhou
Anti-jamming strategy based on game theory in single-channel UAV communication network. FMEC (2021)
Hongkuan Zhou, James Orme-Rogers, Rajgopal Kannan, Viktor K. Prasanna
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings. CoRR (2021)
Hongkuan Zhou, James Orme-Rogers, Rajgopal Kannan, Viktor K. Prasanna
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings. CIKM (2021)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR (2020)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, Efficient and Scalable Training of Graph Neural Networks. CoRR (2020)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, Efficient and Scalable Graph Embedding. IPDPS (2019)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
GraphSAINT: Graph Sampling Based Inductive Learning Method. CoRR (2019)
Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. HPEC (2019)
Hongkuan Zhou, Tao Jiang
Decision Tree Based Sea-Surface Weak Target Detection With False Alarm Rate Controllable. IEEE Signal Process. Lett. 26 (6) (2019)
Yuzhou Li, Yu Zhang, Hongkuan Zhou, Tao Jiang
To Relay or not to Relay: Open Distance and Optimal Deployment for Linear Underwater Acoustic Networks. CoRR (2018)
Yuzhou Li, Yu Zhang, Hongkuan Zhou, Tao Jiang
To Relay or Not to Relay: Open Distance and Optimal Deployment for Linear Underwater Acoustic Networks. IEEE Trans. Commun. 66 (9) (2018)
Hongkuan Zhou, Yuzhou Li, Tao Jiang
Sea Clutter Distribution Modeling: A Kernel Density Estimation Approach. CoRR (2018)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, Efficient and Scalable Graph Embedding. CoRR (2018)
Hongkuan Zhou, Yuzhou Li, Tao Jiang
Sea Clutter Distribution Modeling: A Kernel Density Estimation Approach. WCSP (2018)
Hongkuan Zhou, Tao Jiang, Chen Gong, Yang Zhou
Optimal Estimation in Wireless Sensor Networks With Energy Harvesting. IEEE Trans. Veh. Technol. 65 (11) (2016)