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Shiwen Mao

4 papers hereh-index 3122 citations4 works total

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

author position
  • last author4

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

fields
  • cs.NI2
  • cs.CV1
  • eess.SP1
same name
  • Shiwen Mao — 49 papers, h 20
  • Shiwen Mao — 13 papers
  • Shiwen Mao — 8 papers, h 10
  • Shiwen Mao — 4 papers, h 18
  • Shiwen Mao — 2 papers, h 3
  • Shiwen Mao — 2 papers, h 7

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 citedDeViT: Decomposing Vision Transformers for Collaborative Inference in Edge Devices

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

cs.NI2026

Application-Aware Twin-in-the-Loop Planning for Federated Split Learning over Wireless Edge Networks

Zihao Ding, Beining Wu, Jun Huang +1

We investigate task-success-oriented resource allocation for federated split learning (FSL) at the wireless edge. In this setting, the server must jointly determine bandwidth, tran…

cs.NI2023

Dynamic Routing for Integrated Satellite-Terrestrial Networks: A Constrained Multi-Agent Reinforcement Learning Approach

Yifeng Lyu, Han Hu, Rongfei Fan +3

The integrated satellite-terrestrial network (ISTN) system has experienced significant growth, offering seamless communication services in remote areas with limited terrestrial inf…

eess.SP2023

AI Generated Signal for Wireless Sensing

Hanxiang He, Han Hu, Xintao Huan +3

Deep learning has significantly advanced wireless sensing technology by leveraging substantial amounts of high-quality training data. However, collecting wireless sensing data enco…

cs.CV2023★ 1 cited

DeViT: Decomposing Vision Transformers for Collaborative Inference in Edge Devices

Guanyu Xu, Zhiwei Hao, Yong Luo +3

Recent years have witnessed the great success of vision transformer (ViT), which has achieved state-of-the-art performance on multiple computer vision benchmarks. However, ViT mode…

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