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N. Yu

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • eess.SY2
same name
  • N. Yu — 9 papers, h 8
  • N. Yu — 9 papers
  • N. Yu — 7 papers, h 16
  • N. Yu — 7 papers, h 55
  • N. Yu — 6 papers
  • N. Yu — 6 papers, h 38

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedBatch-Constrained Reinforcement Learning for Dynamic Distribution Network Reconfiguration

9 citations · 14 across the 3 of their papers we have counts for

collaborators

4 papers

eess.SY2020★ 5 cited

Consensus Multi-Agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networks

Yuanqi Gao, Wei Wang, Nanpeng Yu

Volt-VAR control (VVC) is a critical application in active distribution network management system to reduce network losses and improve voltage profile. To remove dependency on inac…

eess.SY2020★ 9 cited

Batch-Constrained Reinforcement Learning for Dynamic Distribution Network Reconfiguration

Yuanqi Gao, Wei Wang, Jie Shi +1

Dynamic distribution network reconfiguration (DNR) algorithms perform hourly status changes of remotely controllable switches to improve distribution system performance. The proble…

cs.LG2019

Improving Supervised Phase Identification Through the Theory of Information Losses

Brandon Foggo, Nanpeng Yu

This paper considers the problem of Phase Identification in power distribution systems. In particular, it focuses on improving supervised learning accuracies by focusing on exploit…

cs.LG2019

Information Losses in Neural Classifiers from Sampling

Brandon Foggo, Nanpeng Yu, Jie Shi +1

This paper considers the subject of information losses arising from the finite datasets used in the training of neural classifiers. It proves a relationship between such losses as…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.