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Yi Wu

4 papers here

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

author position
  • middle author2
  • last author2

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

fields
  • cs.LG3
  • cs.NI1
same name
  • Yi Wu — 11 papers, h 17
  • Yi Wu — 9 papers
  • Yi Wu — 8 papers
  • Yi Wu — 4 papers
  • Yi Wu — 4 papers
  • Yi Wu — 4 papers

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 cited6G-enabled Edge AI for Metaverse: Challenges, Methods, and Future Research Directions

5 citations · 10 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2022

Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition

Kan Xie, Zhe Zhang, Bo Li +4

With the gradual popularization of self-driving, it is becoming increasingly important for vehicles to smartly make the right driving decisions and autonomously obey traffic rules…

cs.NI2022★ 5 cited

6G-enabled Edge AI for Metaverse: Challenges, Methods, and Future Research Directions

Luyi Chang, Zhe Zhang, Pei Li +8

6G-enabled edge intelligence opens up a new era of Internet of Everything and makes it possible to interconnect people-devices-cloud anytime, anywhere. More and more next-generatio…

cs.LG2022★ 3 cited

Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones

Zhe Zhang, Shiyao Ma, Zhaohui Yang +5

Air access networks have been recognized as a significant driver of various Internet of Things (IoT) services and applications. In particular, the aerial computing network infrastr…

cs.LG2021★ 2 cited

Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design

Zhe Zhang, Shiyao Ma, Jiangtian Nie +4

Federated Learning (FL) allows edge devices (or clients) to keep data locally while simultaneously training a shared high-quality global model. However, current research is general…

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