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researcher

Hui Liu

38 papers hereh-index 191.2k citations50 works total

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

author position
  • middle author38

Across the 38 of 38 papers where every author was matched, so the position is known.

fields
  • cs.CV22
  • cs.LG13
  • eess.IV3
same name
  • Hui Liu — 60 papers, h 67
  • Hui Liu — 34 papers, h 12
  • Hui Liu — 33 papers, h 25
  • Hui Liu — 21 papers, h 22
  • Hui Liu — 19 papers, h 6
  • Hui Liu — 17 papers, h 11

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
20192026
most citedAdaptive Attribute and Structure Subspace Clustering Network

52 citations · 194 across the 36 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.LG2020★ 1 cited

Clustering Ensemble Meets Low-rank Tensor Approximation

Yuheng Jia, Hui Liu, Junhui Hou +1

This paper explores the problem of clustering ensemble, which aims to combine multiple base clusterings to produce better performance than that of the individual one. The existing…

cs.CV2020★ 42 cited

Maximum Entropy Subspace Clustering Network

Zhihao Peng, Yuheng Jia, Hui Liu +2

Deep subspace clustering networks have attracted much attention in subspace clustering, in which an auto-encoder non-linearly maps the input data into a latent space, and a fully c…

cs.LG2020

Yet Meta Learning Can Adapt Fast, It Can Also Break Easily

Han Xu, Yaxin Li, Xiaorui Liu +2

Meta learning algorithms have been widely applied in many tasks for efficient learning, such as few-shot image classification and fast reinforcement learning. During meta training,…

cs.LG2020★ 5 cited

Multi-View Spectral Clustering Tailored Tensor Low-Rank Representation

Yuheng Jia, Hui Liu, Junhui Hou +2

This paper explores the problem of multi-view spectral clustering (MVSC) based on tensor low-rank modeling. Unlike the existing methods that all adopt an off-the-shelf tensor low-r…

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