Yang Shu

According to our database, Yang Shu authored at least 27 papers between 2019 and 2025.

Collaborative distances:

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

2025

SwiftTS: A Swift Selection Framework for Time Series Pre-trained Models via Multi-task Meta-Learning.

Tengxue Zhang, Biao Ouyang, Yang Shu, Xinyang Chen, Chenjuan Guo, Bin Yang

CoRR, October, 2025

STAR: Boosting Time Series Foundation Models for Anomaly Detection through State-aware Adapter.

Hanyin Cheng, Ruitong Zhang, Yuning Lu, Peng Chen, Meng Wang, Yang Shu, Bin Yang, Chenjuan Guo

CoRR, October, 2025

CrossAD: Time Series Anomaly Detection with Cross-scale Associations and Cross-window Modeling.

Beibu Li, Qichao Shentu, Yang Shu, Hui Zhang, Ming Li, Ning Jin, Bin Yang, Chenjuan Guo

CoRR, October, 2025

Aurora: Towards Universal Generative Multimodal Time Series Forecasting.

Xingjian Wu, Jianxin Jin, Wanghui Qiu, Peng Chen, Yang Shu, Bin Yang, Chenjuan Guo

CoRR, September, 2025

CC-Time: Cross-Model and Cross-Modality Time Series Forecasting.

Peng Chen, Yihang Wang, Yang Shu, Yunyao Cheng, Kai Zhao, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

CoRR, August, 2025

LightGTS: A Lightweight General Time Series Forecasting Model.

Yihang Wang, Yuying Qiu, Peng Chen, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

CoRR, June, 2025

Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders.

Qichao Shentu, Beibu Li, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation.

Sicong Liu, Yang Shu, Chenjuan Guo, Bin Yang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

EasyTime: Time Series Forecasting Made Easy.

Xiangfei Qiu, Xiuwen Li, Ruiyang Pang, Zhicheng Pan, Xingjian Wu, Liu Yang, Jilin Hu, Yang Shu, Xuesong Lu, Chengcheng Yang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Bin Yang

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

AID-SQL: Adaptive In-Context Learning of Text-to-SQL with Difficulty-Aware Instruction and Retrieval-Augmented Generation.

Xiuwen Li, Qifeng Cai, Yang Shu, Chenjuan Guo, Bin Yang

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification.

Yuxuan Chen, Shanshan Huang, Yunyao Cheng, Peng Chen, Zhongwen Rao, Yang Shu, Bin Yang, Lujia Pan, Chenjuan Guo

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

Enhancing Diversity for Data-free Quantization.

Kai Zhao, Zhihao Zhuang, Miao Zhang, Chenjuan Guo, Yang Shu, Bin Yang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Assessing Pre-Trained Models for Transfer Learning Through Distribution of Spectral Components.

Tengxue Zhang, Yang Shu, Xinyang Chen, Yifei Long, Chenjuan Guo, Bin Yang

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems.

Biao Ouyang, Yingying Zhang, Hanyin Cheng, Yang Shu, Chenjuan Guo, Bin Yang, Qingsong Wen, Lunting Fan, Christian S. Jensen

Proc. VLDB Endow., December, 2024

MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast.

Shiyan Hu, Kai Zhao, Xiangfei Qiu, Yang Shu, Jilin Hu, Bin Yang, Chenjuan Guo

CoRR, 2024

FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting.

Zhe Li, Xiangfei Qiu, Peng Chen, Yihang Wang, Hanyin Cheng, Yang Shu, Jilin Hu, Chenjuan Guo, Aoying Zhou, Qingsong Wen, Christian S. Jensen, Bin Yang

CoRR, 2024

ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning.

Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

CoRR, 2024

Boosting Transferability and Discriminability for Time Series Domain Adaptation.

Mingyang Liu, Xinyang Chen, Yang Shu, Xiucheng Li, Weili Guan, Liqiang Nie

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting.

Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning.

Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

CLIPood: Generalizing CLIP to Out-of-Distributions.

Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long

Proceedings of the International Conference on Machine Learning, 2023

2022

Transferability in Deep Learning: A Survey.

Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long

CoRR, 2022

Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models.

Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long

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

2021

Omni-Training for Data-Efficient Deep Learning.

Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Mingsheng Long

CoRR, 2021

Zoo-Tuning: Adaptive Transfer from A Zoo of Models.

Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long

Proceedings of the 38th International Conference on Machine Learning, 2021

Open Domain Generalization with Domain-Augmented Meta-Learning.

Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019

Transferable Curriculum for Weakly-Supervised Domain Adaptation.

Yang Shu, Zhangjie Cao, Mingsheng Long, Jianmin Wang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019