activity
20202026
most citedEffective End-to-End Learning Framework for Economic Dispatch

5 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Achieving Sample Complexity for Bilinear Systems Identification under Bounded Noises

Hongyu Yi, Chenbei Lu, Jing Yu

This paper studies finite-sample set-membership identification for discrete-time bilinear systems under bounded symmetric log-concave disturbances. Our analysis considers trajector…

cs.LG2025

Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach

Chenbei Lu, Zaiwei Chen, Tongxin Li +2

Traditional reinforcement learning (RL) assumes the agents make decisions based on Markov decision processes (MDPs) with one-step transition models. In many real-world applications…

cs.LG2024★ 2 cited

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

Chenbei Lu, Laixi Shi, Zaiwei Chen +2

Reinforcement Learning (RL) algorithms are known to suffer from the curse of dimensionality, which refers to the fact that large-scale problems often lead to exponentially high sam…

cs.CR2020★ 2 cited

Privacy Preserving in Non-Intrusive Load Monitoring: A Differential Privacy Perspective

Haoxiang Wang, Jiasheng Zhang, Chenbei Lu +1

Smart meter devices enable a better understanding of the demand at the potential risk of private information leakage. One promising solution to mitigating such risk is to inject no…

math.OC2020★ 5 cited

Effective End-to-End Learning Framework for Economic Dispatch

Chenbei Lu, Kui Wang, Chenye Wu

Conventional wisdom to improve the effectiveness of economic dispatch is to design the load forecasting method as accurately as possible. However, this approach can be problematic…