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Guangchen Lan

3 papers here

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

author position
  • sole author1
  • first author1
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CR1
ORCID 0000-0001-7969-7303

identity via Semantic Scholar / OpenAlex

most citedImproved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates

10 citations · 11 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CR2024★ 1 cited

Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis

Mohammadreza Kouchaki, Minglong Zhang, Aly S. Abdalla +3

In the rapidly evolving landscape of 5G technology, safeguarding Radio Frequency (RF) environments against sophisticated intrusions is paramount, especially in dynamic spectrum acc…

cs.LG2023

Communication Efficient and Privacy-Preserving Federated Learning Based on Evolution Strategies

Guangchen Lan

Federated learning (FL) is an emerging paradigm for training deep neural networks (DNNs) in distributed manners. Current FL approaches all suffer from high communication overhead a…

cs.LG2023★ 10 cited

Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates

Guangchen Lan, Han Wang, James Anderson +2

Federated reinforcement learning (FedRL) enables agents to collaboratively train a global policy without sharing their individual data. However, high communication overhead remains…

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