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20172022
most citedDEPTS: Deep Expansion Learning for Periodic Time Series Forecasting

17 citations · 47 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.LG2023

Developing A Fair Individualized Polysocial Risk Score (iPsRS) for Identifying Increased Social Risk of Hospitalizations in Patients with Type 2 Diabetes (T2D)

Yu Huang, Jingchuan Guo, William T Donahoo +7

Background: Racial and ethnic minority groups and individuals facing social disadvantages, which often stem from their social determinants of health (SDoH), bear a disproportionate…

cs.LG20224 cited

Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping

Jiyan He, Xuechen Li, Da Yu +6

Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the tw…

cs.LG20222 cited

Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble

Zhengyu Yang, Kan Ren, Xufang Luo +5

It is challenging for reinforcement learning (RL) algorithms to succeed in real-world applications like financial trading and logistic system due to the noisy observation and envir…

cs.LG202217 cited

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting

Wei Fan, Shun Zheng, Xiaohan Yi +4

Periodic time series (PTS) forecasting plays a crucial role in a variety of industries to foster critical tasks, such as early warning, pre-planning, resource scheduling, etc. Howe…

cs.LG20221 cited

Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting

Lin Huang, Lijun Wu, Jia Zhang +2

Time series forecasting plays a key role in a variety of domains. In a lot of real-world scenarios, there exist multiple forecasting entities (e.g. power station in the solar syste…

cs.LG20211 cited

Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport

Hengxu Lin, Dong Zhou, Weiqing Liu +1

Successful quantitative investment usually relies on precise predictions of the future movement of the stock price. Recently, machine learning based solutions have shown their capa…