HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting.

Shubao Zhao|Ming Jin|Zhaoxiang Hou|Chengyi Yang|Zengxiang Li|Qingsong Wen|Yi Wang


Anthology ID:DBLP:conf/cikm/Zhao0HYLW024
Volume:Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024
Year:2024
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:3352-3362
URL:https://doi.org/10.1145/3627673.3679741
DOI:https://doi.org/10.1145/3627673.3679741
DBLP:conf/cikm/Zhao0HYLW024
BibTeX:
@inproceedings{zhao-2024-himtm, author = {Shubao Zhao and Ming Jin and Zhaoxiang Hou and Chengyi Yang and Zengxiang Li and Qingsong Wen and Yi Wang}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {3352--3362}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679741}, doi = {https://doi.org/10.1145/3627673.3679741} }