2025
TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster.
CoRR, March, 2025
Temporal Coherent Object Flow for Multi-Object Tracking.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
Adaptive Two-Stage Cloud Resource Scaling via Hierarchical Multi-Indicator Forecasting and Bayesian Decision-Making.
CoRR, 2024
A Survey on Diffusion Models for Time Series and Spatio-Temporal Data.
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CoRR, 2024
Autogenic Language Embedding for Coherent Point Tracking.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024
Continuous Invariance Learning.
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Proceedings of the Twelfth International Conference on Learning Representations, 2024
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.
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Proceedings of the Twelfth International Conference on Learning Representations, 2024
Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting.
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Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
DiffusionTrack: Diffusion Model for Multi-Object Tracking.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Continuous Invariance Learning.
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CoRR, 2023
SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies.
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CoRR, 2023
Full Scaling Automation for Sustainable Development of Green Data Centers.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Flow-Based End-to-End Model for Hierarchical Time Series Forecasting via Trainable Attentive-Reconciliation.
Proceedings of the Database Systems for Advanced Applications, 2023
SLOTH: Structured Learning and Task-Based Optimization for Time Series Forecasting on Hierarchies.
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Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation.
CoRR, 2022
A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud.
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Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Memory Augmented State Space Model for Time Series Forecasting.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
End-to-End Modeling of Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow-based Reconciliation.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022
2021
A Graph Regularized Point Process Model For Event Propagation Sequence.
Proceedings of the International Joint Conference on Neural Networks, 2021
2019
A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning.
Proceedings of the International Joint Conference on Neural Networks, 2019
2016
A Context-Aware Method for Top-k Recommendation in Smart TV.
Proceedings of the Web Technologies and Applications - 18th Asia-Pacific Web Conference, 2016