Ruofan Wu

According to our database, Ruofan Wu authored at least 44 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

On provable privacy vulnerabilities of graph representations.

Ruofan Wu, Guanhua Fang, Qiying Pan, Mingyang Zhang, Tengfei Liu, Weiqiang Wang, Wenbiao Zhao

CoRR, 2024

2023

Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device.

Feng Zhang, Ruofan Wu, Jiawei Guan, Zhen Zheng, Xiaoguang Guo, Xiao Zhang, Xiaoyong Du, Xipeng Shen

IEEE Trans. Knowl. Data Eng., October, 2023

A two-stage CNN method for MRI image segmentation of prostate with lesion.

Zixuan Wang, Ruofan Wu, Yanran Xu, Yi Liu, Ruimei Chai, He Ma

Biomed. Signal Process. Control., April, 2023

LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning.

Jintang Li, Jiawang Dan, Ruofan Wu, Jing Zhou, Sheng Tian, Yunfei Liu, Baokun Wang, Changhua Meng, Weiqiang Wang, Yuchang Zhu, Liang Chen, Zibin Zheng

CoRR, 2023

Mitigating Estimation Errors by Twin TD-Regularized Actor and Critic for Deep Reinforcement Learning.

Junmin Zhong, Ruofan Wu, Jennie Si

CoRR, 2023

Privacy-preserving design of graph neural networks with applications to vertical federated learning.

Ruofan Wu, Mingyang Zhang, Lingjuan Lyu, Xiaolong Xu, Xiuquan Hao, Xinyi Fu, Tengfei Liu, Tianyi Zhang, Weiqiang Wang

CoRR, 2023

Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs.

Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen

CoRR, 2023

FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks.

Qiying Pan, Ruofan Wu, Tengfei Liu, Tianyi Zhang, Yifei Zhu, Weiqiang Wang

CoRR, 2023

Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning.

Jintang Li, Wangbin Sun, Ruofan Wu, Yuchang Zhu, Liang Chen, Zibin Zheng

CoRR, 2023

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks.

Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Liang Chen, Zibin Zheng, Baokun Wang, Changhua Meng

CoRR, 2023

Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs.

Jintang Li, Sheng Tian, Ruofan Wu, Liang Zhu, Wenlong Zhao, Changhua Meng, Liang Chen, Zibin Zheng, Hongzhi Yin

CoRR, 2023

DEDGAT: Dual Embedding of Directed Graph Attention Networks for Detecting Financial Risk.

Jiafu Wu, Mufeng Yao, Dong Wu, Mingmin Chi, Baokun Wang, Ruofan Wu, Xin Fu, Changhua Meng, Weiqiang Wang

CoRR, 2023

Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding.

Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin

Proceedings of the ACM Web Conference 2023, 2023

A Long N-step Surrogate Stage Reward for Deep Reinforcement Learning.

Junmin Zhong, Ruofan Wu, Jennie Si

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions.

Ruofan Wu, Jiawei Qiao, Mingzhe Wu, Wen Yu, Ming Zheng, Tengfei Liu, Tianyi Zhang, Weiqiang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders.

Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Self-supervision meets kernel graph neural models: From architecture to augmentations.

Jiawang Dan, Ruofan Wu, Yunpeng Liu, Baokun Wang, Changhua Meng, Tengfei Liu, Tianyi Zhang, Ningtao Wang, Xing Fu, Qi Li, Weiqiang Wang

Proceedings of the IEEE International Conference on Data Mining, 2023

GUARD: Graph Universal Adversarial Defense.

Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

A Momentum Loss Reweighting Method for Improving Recall.

Chenzhi Jiang, Yin Jin, Ningtao Wang, Ruofan Wu, Xing Fu, Weiqiang Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns.

Zaifeng Pan, Zhen Zheng, Feng Zhang, Ruofan Wu, Hao Liang, Dalin Wang, Xiafei Qiu, Junjie Bai, Wei Lin, Xiaoyong Du

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks.

Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Reinforcement Learning Impedance Control of a Robotic Prosthesis to Coordinate With Human Intact Knee Motion.

Ruofan Wu, Minhan Li, Zhikai Yao, Wentao Liu, Jennie Si, He Huang

IEEE Robotics Autom. Lett., 2022

Inferring Human-Robot Performance Objectives During Locomotion Using Inverse Reinforcement Learning and Inverse Optimal Control.

Wentao Liu, Junmin Zhong, Ruofan Wu, Bretta L. Fylstra, Jennie Si, He Helen Huang

IEEE Robotics Autom. Lett., 2022

A New Robotic Knee Impedance Control Parameter Optimization Method Facilitated by Inverse Reinforcement Learning.

Wentao Liu, Ruofan Wu, Jennie Si, He Huang

IEEE Robotics Autom. Lett., 2022

Management and Control of Load Clusters for Ancillary Services Using Internet of Electric Loads Based on Cloud-Edge-End Distributed Computing.

Xin Wu, Lan You, Ruofan Wu, Qi Zhang, Kaixin Liang

IEEE Internet Things J., 2022

Robotic Knee Tracking Control to Mimic the Intact Human Knee Profile Based on Actor-Critic Reinforcement Learning.

Ruofan Wu, Zhikai Yao, Jennie Si, He Helen Huang

IEEE CAA J. Autom. Sinica, 2022

Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems.

Junmin Zhong, Ruofan Wu, Jennie Si

CoRR, 2022

sqSGD: Locally Private and Communication Efficient Federated Learning.

Yan Feng, Tao Xiong, Ruofan Wu, LingJuan Lv, Leilei Shi

CoRR, 2022

MaskGAE: Masked Graph Modeling Meets Graph Autoencoders.

Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang

CoRR, 2022

GUARD: Graph Universal Adversarial Defense.

Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Changhua Meng, Zibin Zheng, Weiqiang Wang

CoRR, 2022

DREW: Efficient Winograd CNN Inference with Deep Reuse.

Ruofan Wu, Feng Zhang, Jiawei Guan, Zhen Zheng, Xiaoyong Du, Xipeng Shen

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

ROLLER: Fast and Efficient Tensor Compilation for Deep Learning.

Hongyu Zhu, Ruofan Wu, Yijia Diao, Shanbin Ke, Haoyu Li, Chen Zhang, Jilong Xue, Lingxiao Ma, Yuqing Xia, Wei Cui, Fan Yang, Mao Yang, Lidong Zhou, Asaf Cidon, Gennady Pekhimenko

Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation, 2022

Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking.

Ruofan Wu, Junmin Zhong, Brent Wallace, Xiang Gao, He Huang, Jennie Si

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TREC: Transient Redundancy Elimination-based Convolution.

Jiawei Guan, Feng Zhang, Jiesong Liu, Hsin-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Design Domain Specific Neural Network via Symbolic Testing.

Hui Li, Xing Fu, Ruofan Wu, Jinyu Xu, Kai Xiao, Xiaofu Chang, Weiqiang Wang, Shuai Chen, Leilei Shi, Tao Xiong, Yuan Qi

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

GRANDE: a neural model over directed multigraphs with application to anti-money laundering.

Ruofan Wu, Boqun Ma, Hong Jin, Wenlong Zhao, Weiqiang Wang, Tianyi Zhang

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

YuenyeungSpTRSV: A Thread-Level and Warp-Level Fusion Synchronization-Free Sparse Triangular Solve.

Feng Zhang, Jiya Su, Weifeng Liu, Bingsheng He, Ruofan Wu, Xiaoyong Du, Rujia Wang

IEEE Trans. Parallel Distributed Syst., 2021

SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing.

Hui Li, Xing Fu, Ruofan Wu, Jinyu Xu, Kai Xiao, Xiaofu Chang, Weiqiang Wang, Shuai Chen, Leilei Shi, Tao Xiong, Yuan Qi

CoRR, 2021

Reinforcement Learning Enabled Automatic Impedance Control of a Robotic Knee Prosthesis to Mimic the Intact Knee Motion in a Co-Adapting Environment.

Ruofan Wu, Minhan Li, Zhikai Yao, Jennie Si, He Huang

CoRR, 2021

Toward Reliable Designs of Data-Driven Reinforcement Learning Tracking Control for Euler-Lagrange Systems.

Zhikai Yao, Jennie Si, Ruofan Wu, Jianyong Yao

CoRR, 2021

Exploring deep reuse in winograd CNN inference.

Ruofan Wu, Feng Zhang, Zhen Zheng, Xiaoyong Du, Xipeng Shen

Proceedings of the PPoPP '21: 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2021

Self-supervised Representation Learning on Dynamic Graphs.

Sheng Tian, Ruofan Wu, Leilei Shi, Liang Zhu, Tao Xiong

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

CapelliniSpTRSV: A Thread-Level Synchronization-Free Sparse Triangular Solve on GPUs.

Jiya Su, Feng Zhang, Weifeng Liu, Bingsheng He, Ruofan Wu, Xiaoyong Du, Rujia Wang

Proceedings of the ICPP 2020: 49th International Conference on Parallel Processing, 2020

2016

Real-time collection and analysis of 3-Kinect v2 skeleton data in a single application.

Serguei A. Mokhov, Miao Song, Jonathan Llewellyn, Jie Zhang, Alexander Charette, Ruofan Wu, Shuiying Ge

Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference, 2016