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Guangyuan Shen

4 papers here

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

author position
  • first author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.GT1
  • cs.IR1
ORCID 0009-0008-7761-2300

identity via Semantic Scholar / OpenAlex

most citedVariance-Reduced Heterogeneous Federated Learning via Stratified Client Selection

6 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

cs.GT2023★ 2 cited

Cross-channel Budget Coordination for Online Advertising System

Guangyuan Shen, Shenjie Sun, Dehong Gao +4

In online advertising (Ad), advertisers are always eager to know how to globally optimize their budget allocation strategies across different channels for more conversions such as…

cs.IR2023★ 1 cited

EdgeNet : Encoder-decoder generative Network for Auction Design in E-commerce Online Advertising

Guangyuan Shen, Shengjie Sun, Dehong Gao +3

We present a new encoder-decoder generative network dubbed EdgeNet, which introduces a novel encoder-decoder framework for data-driven auction design in online e-commerce advertisi…

cs.LG2022★ 2 cited

Fast Heterogeneous Federated Learning with Hybrid Client Selection

Guangyuan Shen, Dehong Gao, Duanxiao Song +5

Client selection schemes are widely adopted to handle the communication-efficient problems in recent studies of Federated Learning (FL). However, the large variance of the model up…

cs.LG2022★ 6 cited

Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection

Guangyuan Shen, Dehong Gao, Libin Yang +4

Client selection strategies are widely adopted to handle the communication-efficient problem in recent studies of Federated Learning (FL). However, due to the large variance of the…

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