Yuanshao Zhu

According to our database, Yuanshao Zhu authored at least 18 papers between 2020 and 2024.

Collaborative distances:

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

2024

Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond.

Wei Chen, Yuxuan Liang, Yuanshao Zhu, Yanchuan Chang, Kang Luo, Haomin Wen, Lei Li, Yanwei Yu, Qingsong Wen, Chao Chen, Kai Zheng, Yunjun Gao, Xiaofang Zhou, Yu Zheng

CoRR, 2024

Large Language Model Distilling Medication Recommendation Model.

Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu, Zijian Zhang, Feng Tian, Yefeng Zheng

CoRR, 2024

2023

Traffic Prediction With Transfer Learning: A Mutual Information-Based Approach.

Yunjie Huang, Xiaozhuang Song, Yuanshao Zhu, Shiyao Zhang, James J. Q. Yu

IEEE Trans. Intell. Transp. Syst., August, 2023

MOELoRA: An MOE-based Parameter Efficient Fine-Tuning Method for Multi-task Medical Applications.

Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu, Derong Xu, Feng Tian, Yefeng Zheng

CoRR, 2023

Enhancing Traffic Prediction with Learnable Filter Module.

Yuanshao Zhu, Yongchao Ye, Xiangyu Zhao, James J. Q. Yu

CoRR, 2023

Diffusion Model for GPS Trajectory Generation.

Yuanshao Zhu, Yongchao Ye, Xiangyu Zhao, James J. Q. Yu

CoRR, 2023

AutoDenoise: Automatic Data Instance Denoising for Recommendations.

Weilin Lin, Xiangyu Zhao, Yejing Wang, Yuanshao Zhu, Wanyu Wang

Proceedings of the ACM Web Conference 2023, 2023

DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model.

Yuanshao Zhu, Yongchao Ye, Shiyao Zhang, Xiangyu Zhao, James Yu

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

SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis.

Yuanshao Zhu, Yongchao Ye, Ying Wu, Xiangyu Zhao, James Jian Qiao Yu

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

Data-Driven Methods for Travel Time Estimation: A Survey.

Zhipeng Zheng, Yongchao Ye, Yuanshao Zhu, Shiyao Zhang, James J. Q. Yu

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022

Resource-Constrained Federated Edge Learning With Heterogeneous Data: Formulation and Analysis.

Yi Liu, Yuanshao Zhu, James J. Q. Yu

IEEE Trans. Netw. Sci. Eng., 2022

Cross-Area Travel Time Uncertainty Estimation From Trajectory Data: A Federated Learning Approach.

Yuanshao Zhu, Yongchao Ye, Yi Liu, James J. Q. Yu

IEEE Trans. Intell. Transp. Syst., 2022

Semi-Supervised Federated Learning for Travel Mode Identification From GPS Trajectories.

Yuanshao Zhu, Yi Liu, James J. Q. Yu, Xingliang Yuan

IEEE Trans. Intell. Transp. Syst., 2022

CatETA: A Categorical Approximate Approach for Estimating Time of Arrival.

Yongchao Ye, Yuanshao Zhu, Christos Markos, James J. Q. Yu

IEEE Trans. Intell. Transp. Syst., 2022

Toward Crowdsourced Transportation Mode Identification: A Semisupervised Federated Learning Approach.

Chenhan Zhang, Yuanshao Zhu, Christos Markos, Shui Yu, James J. Q. Yu

IEEE Internet Things J., 2022

2021

FedOVA: One-vs-All Training Method for Federated Learning with Non-IID Data.

Yuanshao Zhu, Christos Markos, Ruihui Zhao, Yefeng Zheng, James J. Q. Yu

Proceedings of the International Joint Conference on Neural Networks, 2021

Improving Transportation Mode Identification with Limited GPS Trajectories.

Yuanshao Zhu, Christos Markos, James J. Q. Yu

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

2020

Robust Federated Learning Approach for Travel Mode Identification from Non-IID GPS Trajectories.

Yuanshao Zhu, Shuyu Zhang, Yi Liu, Dusit Niyato, James J. Q. Yu

Proceedings of the 26th IEEE International Conference on Parallel and Distributed Systems, 2020