KDD 2025 | (2月轮)时间序列（Time Series）论文总结

时空探索之旅

发布于 2025-06-23 13:29:08

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KDD 2025将在2025年8月3号到7号在加拿大多伦多举行，本文总结了KDD 2025(February Cycle)有关时间序列（Time Series）相关文章，共计35篇，其中1-32为Research Track，33-35为ADS Track。如有疏漏，欢迎补充！

时间序列Topic：预测，插补，异常检测，表示学习，因果，大语言模型，测试时适应等

1. FAT: Frequency-Aware Pretraining for Enhanced Time-Series Representation Learning2. Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates3. TimeCapsule: Solving the Jigsaw Puzzle of Long-Term Time Series Forecasting with Compressed Predictive Representations4. CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements5. Beyond Fixed Variables: Expanding-variate Time Series Forecasting via Flat Scheme and Spatio-temporal Focal Learning6. Stochastic Diffusion: A Diffusion Based Model for Stochastic Time Series Forecasting7. Semantics-Aware Patch Encoding and Hierarchical Dependency Modeling for Long-Term Time Series Forecasting8. SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting9. Performative Time-Series Forecasting10. CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables11. CMA: A Unified Contextual Meta-Adaptation Methodology for Time-Series Denoising and Prediction12. BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models13. Generalized Discords for Time Series Anomaly Detection with Flexible Subsequence Lengths14. MSHTrans: Multi-Scale Hypergraph Transformer with Time-Series Decomposition for Temporal Anomaly Detection15. Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning16. Diffusion-Guided Diversity for Single Domain Generalization in Time Series Classification17. Learning Reliable and Intuitive Temporal Logic Rules for Interpretable Time Series Classification18. Loss or Gain: Hierarchical Conditional Information Bottleneck Approach for Incomplete Time Series Classification19. Mitigating Data Imbalance in Time Series Classification Based on Counterfactual Minority Samples Augmentation20. Fully Quanvolutional Networks for Time Series Classification21. FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series Classification22. MTM: A Multi-Scale Token Mixing Transformer for Irregular Multivariate Time Series Classification23. Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment24. Robust and Explainable Detector of Time Series Anomaly via Augmenting Multiclass Pseudo-Anomalies25. Pre-training Time Series Models with Stock Data Customization26. SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation27. TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation28. Temporal Restoration and Spatial Rewiring for Source-Free Multivariate Time Series Domain Adaptation29. Test-Time Training with Diversified Local Aggregation Consistency for Mortality Prediction using Clinical Time Series30. Bi-Modal Learning for Networked Time Series31. Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series32. FRT: Flow-based Reconcile Transformer for Hierarchical Time Series33. Mitigating Source Label Dependency in Time-Series Domain Adaptation under Label Shifts34. Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection35. Timing is important: Risk-aware Fund Allocation based on Time-Series Forecasting

说明:如果论文总结中有（模型）图，则论文已经在网络上公开（arXiv，Openreview等）。目前doi的链接官网表示要在8月3日后公布。（"DOI links will be available by August 3rd, please check back then to access the direct links below"）

Research

1 FAT: Frequency-Aware Pretraining for Enhanced Time-Series Representation Learning

链接：https://doi.org/10.1145/3711896.3736952

作者：Rui Cheng (School of Finance, Southwestern University of Finance and Economics); Xiangfei Jia (School of Computer and Artificial Intelligence, Southwestern University of Finance and Economics); Qing Li (Research Institute for Digital Economy and Interdisciplinary Sciences, Southwestern University of Finance and Economics); Rong Xing (School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics); Jiwen Huang (Fintech Innovation Center, Southwestern University of Finance and Economics); Yu Zheng (School of Finance, Southwestern University of Finance and Economics); Zhilong Xie (School of Management Science and Engineering, Southwestern University of Finance and Economics)

关键词：表示学习

2 Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates

链接：https://doi.org/10.1145/3711896.3737046

作者：Chengqing Yu (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety, University of Chinese Academy of Sciences); Fei Wang (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety, University of Chinese Academy of Sciences); Chuanguang Yang (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Zezhi Shao (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Tao Sun (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Tangwen Qian (Institute of Computing Technology, Chinese Academy of ScienceS,State Key Laboratory of AI Safety); Wei Wei (School of Computer Science and Technology, Huazhong University of Science and Technology); Zhulin An (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety, University of Chinese Academy of Sciences); Yongjun Xu (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety, University of Chinese Academy of Sciences)

关键词：预测，表示学习，多视图

3 TimeCapsule: Solving the Jigsaw Puzzle of Long-Term Time Series Forecasting with Compressed Predictive Representations

链接：https://doi.org/10.1145/3711896.3737157

作者：Yihang Lu (Hefei Institutes of Physical Science, Chinese Academy of Sciences,University of Science and Technology of China); Yangyang Xu (Hefei Institutes of Physical Science, Chinese Academy of Sciences,University of Science and Technology of China); Qitao Qin (University of Science and Technology of China); Xianwei Meng (Hefei Institutes of Physical Science, Chinese Academy of Sciences)

关键词：预测，压缩预测

4 CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements

链接：https://doi.org/10.1145/3711896.3736872

作者：Yang Zhang (Southwestern University of Finance and Economics); Wenbo Yang (Southwestern University of Finance and Economics); Jun Wang (Southwestern University of Finance and Economics); Qiang Ma (Kyoto Institute of Technology); Jie Xiong (Southwestern University of Finance and Economics)

关键词：预测，因果，多模态

5 Beyond Fixed Variables: Expanding-variate Time Series Forecasting via Flat Scheme and Spatio-temporal Focal Learning

链接：https://doi.org/10.1145/3711896.3736854

作者：Minbo Ma (School of Computing and Artificial Intelligence, Southwest Jiaotong University,Faculty of Mathematics and Computer Science, FernUniversität in Hagen); Kai Tang (School of Computing and Artificial Intelligence, Southwest Jiaotong University); Huan Li (Zhejiang University); Fei Teng (School of Computing and Artificial Intelligence, Southwest Jiaotong University,Engineering Research Center of Sustainable Urban Intelligent Transportation, Ministry of Education); Dalin Zhang (Department of Computer Science, Aalborg University); Tianrui Li (School of Computing and Artificial Intelligence, Southwest Jiaotong University,Engineering Research Center of Sustainable Urban Intelligent Transportation, Ministry of Education)

关键词：预测，时空焦点

6 Stochastic Diffusion: A Diffusion Based Model for Stochastic Time Series Forecasting

链接：https://doi.org/10.1145/3711896.3737137

作者：Yuansan Liu (School of Computing and Information Systems, The University of Melbourne); Sudanthi Wijewickrema (Department of Surgery (Otolaryngology), The University of Melbourne); Dongting Hu (School of Mathematics and Statistics, The University of Melbourne); Christofer Bester (Department of Surgery (Otolaryngology), The University of Melbourne); Stephen O’Leary (Department of Surgery (Otolaryngology), The University of Melbourne); James Bailey (School of Computing and Information Systems, The University of Melbourne)

关键词：预测，扩散模型

7 Semantics-Aware Patch Encoding and Hierarchical Dependency Modeling for Long-Term Time Series Forecasting

链接：https://doi.org/10.1145/3711896.3737123

作者：Sijia Peng (Shanghai Key Lab of Data Science, College of Computer Science and Artificial Intelligence, Fudan University); Yun Xiong (Shanghai Key Lab of Data Science, College of Computer Science and Artificial Intelligence, Fudan University); Yangyong Zhu (Shanghai Key Lab of Data Science, College of Computer Science and Artificial Intelligence, Fudan University,Shanghai Data Research Institute); Zhiqiang Shen (Machine Learning Department, Mohamed bin Zayed University of Artificial Intelligence)

关键词：预测，语义感知

8 SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting

链接：https://doi.org/10.1145/3711896.3737119

作者：Zixuan Weng (The Hong Kong University of Science and Technology (Guangzhou)); Jindong Han (Academy of Interdisciplinary Studies, The Hong Kong University of Science and Technology); Wenzhao Jiang (The Hong Kong University of Science and Technology (Guangzhou)); Hao Liu (The Hong Kong University of Science and Technology (Guangzhou))

关键词：预测，状态空间模型

9 Performative Time-Series Forecasting

链接：https://doi.org/10.1145/3711896.3737078

作者：Zhiyuan Zhao (College of Computing, Georgia Institute of Technology); Haoxin Liu (College of Computing, Georgia Institute of Technology); Alexander Rodríguez (Computer Science and Engineering, University of Michigan); B. Aditya Prakash (College of Computing, Georgia Institute of Technology)

关键词：预测，分布偏移

10 CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables

链接：https://doi.org/10.1145/3711896.3736899

作者：Pengfei Zhou (University of Science and Technology of China); Yunlong Liu (University of Science and Technology of China); Junli Liang (University of Science and Technology of China); Qi Song (University of Science and Technology of China,Deqing Alpha Innovation Institute); Xiangyang Li (University of Science and Technology of China,Deqing Alpha Innovation Institute)

关键词：预测，协变量（外生变量）

11 CMA: A Unified Contextual Meta-Adaptation Methodology for Time-Series Denoising and Prediction

链接：https://doi.org/10.1145/3711896.3736881

作者：Haiqi Jiang (School of Artificial Intelligence, South China Normal University); Ying Ding (International Business School, South China Normal University); Chenjie Pan (School of Artificial Intelligence, South China Normal University); Aimin Huang (Board of Directors, Hangzhou Rose Technology Co., Ltd); Rui Chen (International Business College, South China Normal University); Chenyou Fan (School of Artificial Intelligence, South China Normal University)

关键词：预测，去噪

12 BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models

链接：https://doi.org/10.1145/3711896.3736860

作者：Zezhi Shao (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Yujie Li (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Fei Wang (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Chengqing Yu (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Yisong Fu (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Tangwen Qian (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Bin Xu (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Boyu Diao (Institute of Computing Technology, Chinese Academy of Sciences.,State Key Laboratory of AI Safety); Yongjun Xu (Institute of Computing Technology, Chinese Academy of Sciences,State Key Laboratory of AI Safety); Xueqi Cheng (Institute of Computing Technology, Chinese Academy,State Key Laboratory of AI Safety)

关键词：预测，通用模型

13 Generalized Discords for Time Series Anomaly Detection with Flexible Subsequence Lengths

链接：https://doi.org/10.1145/3711896.3736977

作者：Makoto Imamura (School of Information and Telecommunication Engineering, Tokai University Educational System)

关键词：异常检测

14 MSHTrans: Multi-Scale Hypergraph Transformer with Time-Series Decomposition for Temporal Anomaly Detection

链接：https://doi.org/10.1145/3711896.3737057

作者：Zhaoliang Chen (Hong Kong Baptist University); Zhihao Wu (Zhejiang University); William K. Cheung (Hong Kong Baptist University); Hong-Ning Dai (Hong Kong Baptist University); Byron Choi (Hong Kong Baptist University); Jiming Liu (Hong Kong Baptist University)

关键词：异常检测，超图，Transformer

15 Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning

链接：https://doi.org/10.1145/3711896.3737174

作者：Kai Zhao (Aalborg University); Zhihao Zhuang (East China Normal University); Chenjuan Guo (East China Normal University); Hao Miao (Aalborg University); Christian S. Jensen (Aalborg University); Yunyao Cheng (Aalborg University); Bin Yang (East China Normal University)

关键词：异常预测，对比学习

16 Diffusion-Guided Diversity for Single Domain Generalization in Time Series Classification

链接：https://doi.org/10.1145/3711896.3736909

作者：Junru Zhang (Computer Science and Technology, Zhejiang University); Lang Feng (College of Computing and Data Science, Nanyang Technological University); Xu Guo (Department of Intelligent Systems, KTH Royal Institute of Technology); Han Yu (College of Computing and Data Science, Nanyang Technological University); Yabo Dong (Computer Science and Technology, Zhejiang University); Duanqing Xu (Computer Science and Technology, Zhejiang University)

关键词：分类，扩散模型，域泛化

17 Learning Reliable and Intuitive Temporal Logic Rules for Interpretable Time Series Classification

链接：https://doi.org/10.1145/3711896.3737022

作者：Yang Wang (Institute of Software, Chinese Academy of Sciences,University of Chinese Academy of Sciences); Jiaqi Zhu (Institute of Software, Chinese Academy of Sciences,University of Chinese Academy of Sciences); Miaomiao Li (Institute of Software, Chinese Academy of Sciences,University of Chinese Academy of Sciences); Jiang Liu (Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences); Yilin Li (Institute of Software, Chinese Academy of Sciences,University of the Chinese Academy of Sciences); Yi Yang (Institute of Software, Chinese Academy of Sciences); Jiafan Li (Institute of Software, Chinese Academy of Sciences,University of the Chinese Academy of Sciences); Hongan Wang (Institute of software, Chinese Academy of Sciences,University of the Chinese Academy of Sciences)

关键词：分类，可解释性

18 Loss or Gain: Hierarchical Conditional Information Bottleneck Approach for Incomplete Time Series Classification

链接：https://doi.org/10.1145/3711896.3737033

作者：Shuo Zhang (School of Computer Science and Technology, Beijing Jiaotong University); Jing Wang (School of Computer Science and Technology, Beijing Jiaotong University,Key Laboratory of Big Data & Artificial Intelligence in Transportation, Ministry of Education); Shiqin Nie (School of Computer Science and Technology, Beijing Jiaotong University); Jinghang Yue (School of Computer Science and Technology, Beijing Jiaotong University); Weikang Zhu (School of Computer Science and Technology, Beijing Jiaotong University); Youfang Lin (School of Computer Science and Technology, Beijing Jiaotong University,Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence)

关键词：分类，信息瓶颈

19 Mitigating Data Imbalance in Time Series Classification Based on Counterfactual Minority Samples Augmentation

链接：https://doi.org/10.1145/3711896.3737049

作者：Lei Wang (School of Big Data and Software Engineering, Chongqing University); Shanshan Huang (School of Big Data and Software Engineering, Chongqing University); Chunyuan Zheng (School of Mathematical Sciences, Peking University); Jun Liao (School of Big Data and Software Engineering, Chongqing University); Xiaofei Zhu (School of Computer Science and Engineering, Chongqing University of Technology); Haoxuan Li (Center for Data Science, Peking University); Li Liu (School of Big Data and Software Engineering, Chongqing University)

关键词：分类，反事实少样本增强

20 Fully Quanvolutional Networks for Time Series Classification

链接：https://doi.org/10.1145/3711896.3736972

作者：Nabil Anan Orka (The University of Queensland); Ehtashamul Haque (BRAC University); Md. Abdul Awal (The University of Queensland); Mohammad Ali Moni (Charles Sturt University,Washington University of Science and Technology)

关键词：分类，全卷积

21 FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series Classification

链接：https://doi.org/10.1145/3711896.3736969

作者：Tian Tian (Alibaba-NTU Singapore Joint Research Institute, Interdisciplinary Graduate Programme, Nanyang Technological University); Chunyan Miao (College of Computing and Data Science, Nanyang Technological University); Hangwei Qian (CFAR, A*STAR)

关键词：分类，对比学习，频域细化

22 MTM: A Multi-Scale Token Mixing Transformer for Irregular Multivariate Time Series Classification

链接：https://doi.org/10.1145/3711896.3737058

作者：Shuhan Zhong (Department of Computer Science and Engineering, The Hong Kong University of Science and Technology); Weipeng Zhuo (Department of Computer Science, Beijing Normal-Hong Kong Baptist University); Sizhe Song (Department of Computer Science and Engineering, The Hong Kong University of Science and Technology); Guanyao Li (Guangzhou Urban Planning and Design Survey Research Institute); Zhongyi Yu (Department of Computer Science, Beijing Normal-Hong Kong Baptist University); S.-H. Gary Chan (Department of Computer Science and Engineering, The Hong Kong University of Science and Technology)

关键词：分类，多尺度混合

23 Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment

链接：https://doi.org/10.1145/3711896.3737169

作者：Liangwei Nathan Zheng (The University of Adelaide); Chang Dong (The University of Adelaide); Wei Emma Zhang (The University of Adelaide); Lin Yue (The University of Adelaide); Miao Xu (The University of Queensland); Olaf Maennel (The University of Adelaide); Weitong Chen (The University of Adelaide)

关键词：时序分析，大语言模型，模态对齐

24 Robust and Explainable Detector of Time Series Anomaly via Augmenting Multiclass Pseudo-Anomalies

链接：https://doi.org/10.1145/3711896.3737110

作者：Kohei Obata (SANKEN, University of Osaka); Yasuko Matsubara (SANKEN, University of Osaka); Yasushi Sakurai (SANKEN, University of Osaka)

关键词：异常检测，可解释性，稳健性

25 Pre-training Time Series Models with Stock Data Customization

链接：https://doi.org/10.1145/3711896.3737005

作者：Mengyu Wang (School of Informatics, University of Edinburgh); Tiejun Ma (School of Informatics, University of Edinburgh); Shay B. Cohen (School of Informatics, University of Edinburgh)

关键词：预训练时序模型，股票数据

26 SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation

链接：https://doi.org/10.1145/3711896.3737135

作者：Hongfan Gao (East China Normal University); Wangmeng Shen (East China Normal University); Xiangfei Qiu (East China Normal University); Ronghui Xu (East China Normal University); Bin Yang (East China Normal University); Jilin Hu (East China Normal University,Engineering Research Center of Blockchain Data Management (East China Normal University), Ministry of Education)

关键词：插补，扩散模型，状态空间模型

27 TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation

链接：https://doi.org/10.1145/3711896.3737147

作者：Bowen Deng (Peking University); Chang Xu (Microsoft Research); Hao Li (University of Manchester); Yu-hao Huang (Nanjing University); Min Hou (Hefei University of Technology); Jiang Bian (Microsoft Research Asia)

关键词：生成，扩散模型

28 Temporal Restoration and Spatial Rewiring for Source-Free Multivariate Time Series Domain Adaptation

链接：https://doi.org/10.1145/3711896.3737150

作者：Peiliang Gong (Nanjing University of Aeronautics and Astronautics); Yucheng Wang (Institute for Infocomm Research, Agency for Science Technology and Research (A\STAR),Nanyang Technological University); Min Wu (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR)); Zhenghua Chen (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR),Centre for Frontier AI Research, Agency for Science Technology and Research (A*STAR)); Xiaoli Li (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR),Centre for Frontier AI Research, Agency for Science Technology and Research (A*STAR)); Daoqiang Zhang (Nanjing University of Aeronautics and Astronautics)

关键词：域适应，图神经网络

29 Test-Time Training with Diversified Local Aggregation Consistency for Mortality Prediction using Clinical Time Series

链接：https://doi.org/10.1145/3711896.3737151

作者：Jingwen Xu (Department of Computer Science, Hong Kong Baptist University); Fei Lyu (Department of Computer Science, Hong Kong Baptist University); Pong C. Yuen (Department of Computer Science, Hong Kong Baptist University)

关键词：临床时间序列，一致性测试时间训练

30 Bi-Modal Learning for Networked Time Series

链接：https://doi.org/10.1145/3711896.3736856

作者：Youngeun Nam (School of Computing, Korea Advanced Institute of Science and Technology); Jihye Na (School of Computing, Korea Advanced Institute of Science & Technology); Susik Yoon (Computer Science and Engineering, Korea University); Hwanjun Song (Industrial and Systems Engineering, Korea Advanced Institute of Science & Technology); Jae-Gil Lee (School of Computing, Korea Advanced Institute of Science and Technology); Byung Suk Lee (University of Vermont)

关键词：网络时间序列，双模态

31 Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series

链接：https://doi.org/10.1145/3711896.3737171

作者：Weijia Zhang (HKUST (GZ)); Chenlong Yin (HKUST (GZ)); Hao Liu (HKUST (GZ) & HKUST); Hui Xiong (HKUST (GZ) & HKUST)

关键词：不规则时间序列，预训练语言模型

32 Mitigating Source Label Dependency in Time-Series Domain Adaptation under Label Shifts

链接：https://doi.org/10.1145/3711896.3737050

作者：Jihye Na (School of Computing, Korea Advanced Institute of Science & Technology); Youngeun Nam (School of Computing, Korea Advanced Institute of Science and Technology); Junhyeok Kang (LG AI Research); Jae-Gil Lee (School of Computing, Korea Advanced Institute of Science and Technology)

关键词：时间序列域自适应

ADS Track

33 FRT: Flow-based Reconcile Transformer for Hierarchical Time Series

链接：https://doi.org/10.1145/3711896.3737224

作者：Shiyu Wang (Ant Group); Wei Lu (Ant Group); Jiawei Li (Uppsala University); Xiaoming Shi (Ant Group); Xinyue Zhong (Ant Group); Zhou Ye (Alibaba); Ming Jin (Griffith University); Qingsong Wen (Squirrel Ai Learning)

关键词：流，分层时间序列

34 Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

链接：https://doi.org/10.1145/3711896.3737239

作者：Jun Liu (CS, University of Chinese Academy of Sciences); Chaoyun Zhang (Microsoft); Jiaxu Qian (Microsoft); Minghua Ma (Microsoft); Si Qin (Microsoft); Chetan Bansal (Microsoft); Qingwei Lin (Microsoft); Saravan Rajmohan (Microsoft); Dongmei Zhang (Microsoft)

关键词：异常检测，大语言模型

35 Timing is important: Risk-aware Fund Allocation based on Time-Series Forecasting

链接：https://doi.org/10.1145/3711896.3737268

作者：Fuyuan Lyu (School of Computer Science, McGill University,Mila – Quebec AI Institute); Linfeng Du (School Of Computer Science, McGill University); Yunpeng Weng (FiT, Tencent); Qiufang Ying (FiT, Tencent); Zhiyan Xu (FiT, Tencent); Wen Zou (FiT, Tencent); Haolun Wu (School of Computer Science, McGill University,Mila – Quebec AI Institute); Xiuqiang He (Big data and Internet, Shenzhen Technology University); Xing Tang (Big data and Internet, Shenzhen Technology University)

关键词：预测，风险感知