| iTransformer: Inverted transformers are effective for time series forecasting Y Liu, T Hu, H Zhang, H Wu, S Wang, L Ma, M Long International Conference on Learning Representations (ICLR 2024), 2024 | 621 | 2024 |
| Time-llm: Time series forecasting by reprogramming large language models M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ... International Conference on Learning Representations (ICLR 2024), 2024 | 428 | 2024 |
| Timemixer: Decomposable multiscale mixing for time series forecasting S Wang, H Wu, X Shi, T Hu, H Luo, L Ma, JY Zhang, J Zhou International Conference on Learning Representations (ICLR 2024), 2024 | 136 | 2024 |
| A hybrid feature selection algorithm: Combination of symmetrical uncertainty and genetic algorithms BN Jiang, X Ding, L Ma, Y He, T Wang, W Xie The second international symposium on optimization and systems biology, 152-157, 2008 | 64 | 2008 |
| An unsupervised feature selection algorithm: Laplacian score combined with distance-based entropy measure R Liu, N Yang, X Ding, L Ma 2009 third international symposium on intelligent information technology …, 2009 | 55 | 2009 |
| A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud S Xue, C Qu, X Shi, C Liao, S Zhu, X Tan, L Ma, S Wang, S Wang, Y Hu, ... Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 42 | 2022 |
| A survey on diffusion models for time series and spatio-temporal data Y Yang, M Jin, H Wen, C Zhang, Y Liang, L Ma, Y Wang, C Liu, B Yang, ... arXiv preprint arXiv:2404.18886, 2024 | 34 | 2024 |
| Intelligent techniques for cigarette formula design TJ Feng, LT Ma, XQ Ding, N Yang, X Xiao Mathematics and Computers in Simulation 77 (5-6), 476-486, 2008 | 16 | 2008 |
| A graph regularized point process model for event propagation sequence S Xue, X Shi, H Hao, L Ma, J Zhang, S Wang, S Wang 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 11 | 2021 |
| End-to-end modeling of hierarchical time series using autoregressive transformer and conditional normalizing flow-based reconciliation S Wang, F Zhou, Y Sun, L Ma, J Zhang, Y Zheng 2022 IEEE International Conference on Data Mining Workshops (ICDMW), 1087-1094, 2022 | 10 | 2022 |
| Full scaling automation for sustainable development of green data centers S Wang, Y Sun, X Shi, S Zhu, LT Ma, J Zhang, Y Zheng, J Liu Proceedings of the Thirty-Second International Joint Conference on …, 2023 | 6 | 2023 |
| Genetic algorithm for optimization of tobacco-group formulas design HL Gong, XQ Ding, LT Ma The Proceedings of the Multiconference on" Computational Engineering in …, 2006 | 5 | 2006 |
| SLOTH: structured learning and task-based optimization for time series forecasting on hierarchies F Zhou, C Pan, L Ma, Y Liu, S Wang, J Zhang, X Zhu, X Hu, Y Hu, Y Zheng, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11417 …, 2023 | 4 | 2023 |
| Continuous Invariance Learning Y Lin, F Zhou, L Tan, L Ma, J Liu, Y He, Y Yuan, Y Liu, J Zhang, Y Yang, ... International Conference on Learning Representations (ICLR 2024), 2024 | 3 | 2024 |
| Multiscale representation enhanced temporal flow fusion model for long-term workload forecasting S Wang, Z Chu, Y Sun, Y Liu, Y Guo, Y Chen, H Jian, L Ma, X Lu, J Zhou Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 2 | 2024 |
| Adaptive two-stage cloud resource scaling via hierarchical multi-indicator forecasting and bayesian decision-making Y Luo, S Wang, Z Yu, W Lu, X Gao, L Ma, G Chen arXiv preprint arXiv:2408.01000, 2024 | 2 | 2024 |
| Flow-Based End-to-End Model for Hierarchical Time Series Forecasting via Trainable Attentive-Reconciliation S Wang, Y Sun, Y Wang, F Zhou, LT Ma, J Zhang, YF Zheng International Conference on Database Systems for Advanced Applications, 167-176, 2023 | 2 | 2023 |
| Memory Augmented State Space Model for Time Series Forecasting Y Sun, L Ma, Y Liu, S Wang, J Zhang, YF Zheng, H Yun, L Lei, Y Kang, ... Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 2 | 2022 |
| YONG LIU Y Liu, H Zhang, C Li, X Huang, J Wang, M Long, G Qin, T Hu, H Wu, ... | 2 | 2017 |
| Supervised Manifold Learning for NIR Modeling of Cigarette Brand Identification Y He, XQ Ding, LT Ma Advanced Materials Research 457, 1258-1263, 2012 | 2 | 2012 |
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