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Yalin Wang

25 papers hereh-index 416.3k citations226 works total

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

author position
  • middle author6
  • last author18

Across the 24 of 25 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG6
  • eess.IV2
  • physics.med-ph2
  • q-bio.NC2
  • cs.CG1
same name
  • Yalin Wang — 39 papers, h 10
  • Yalin Wang — 6 papers, h 2
  • Yalin Wang — 5 papers, h 7
  • Yalin Wang — 4 papers, h 2
  • Yalin Wang — 3 papers, h 4
  • Yalin Wang — 2 papers, h 8

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

activity
20162023
most citedGraph Neural Networks for User Identity Linkage

16 citations · 59 across the 25 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

eess.IV2019

Geometric Brain Surface Network For Brain Cortical Parcellation

Wen Zhang, Yalin Wang

A large number of surface-based analyses on brain imaging data adopt some specific brain atlases to better assess structural and functional changes in one or more brain regions. In…

cs.CV2019★ 3 cited

Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML

Jie Zhang, Junting Zhang, Shalini Ghosh +4

Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community. The aim of lifelong…

cs.SI2019★ 16 cited

Graph Neural Networks for User Identity Linkage

Wen Zhang, Kai Shu, Huan Liu +1

The increasing popularity and diversity of social media sites has encouraged more and more people to participate in multiple online social networks to enjoy their services. Each us…

cs.CV2019

MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression

Jie Zhang, Xiaolong Wang, Dawei Li +3

State-of-the-art deep model compression methods exploit the low-rank approximation and sparsity pruning to remove redundant parameters from a learned hidden layer. However, they pr…

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