most citedHow to Leverage Diverse Demonstrations in Offline Imitation Learning

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cs.LG2026

Cloud-Edge Collaborative Large Models for Robust Photovoltaic Power Forecasting

Nan Qiao, Shuning Wang, Sijing Duan +5

Photovoltaic (PV) power forecasting in edge-enabled grids requires balancing forecasting accuracy, robustness under weather-driven distribution shifts, and strict latency constrain…

cs.LG2024

OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning

Sheng Yue, Xingyuan Hua, Ju Ren +3

In this paper, we study offline-to-online Imitation Learning (IL) that pretrains an imitation policy from static demonstration data, followed by fast finetuning with minimal enviro…

cs.LG2024★ 1 cited

How to Leverage Diverse Demonstrations in Offline Imitation Learning

Sheng Yue, Jiani Liu, Xingyuan Hua +4

Offline Imitation Learning (IL) with imperfect demonstrations has garnered increasing attention owing to the scarcity of expert data in many real-world domains. A fundamental probl…

cs.LG2024

Federated Offline Policy Optimization with Dual Regularization

Sheng Yue, Zerui Qin, Xingyuan Hua +2

Federated Reinforcement Learning (FRL) has been deemed as a promising solution for intelligent decision-making in the era of Artificial Internet of Things. However, existing FRL ap…

cs.LG2024

Momentum-Based Federated Reinforcement Learning with Interaction and Communication Efficiency

Sheng Yue, Xingyuan Hua, Lili Chen +1

Federated Reinforcement Learning (FRL) has garnered increasing attention recently. However, due to the intrinsic spatio-temporal non-stationarity of data distributions, the current…