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researcher

Junbin Gao

Discipline of Business Analytics, The University of Sydney Business School, The University of Sydney, Sydney, NSW, Australia

18 papers hereh-index 457.6k citations336 works total

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

author position
  • middle author11
  • last author5

Across the 16 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • cs.LG4
  • cs.DS1
  • stat.ML1
affiliations
  • Discipline of Business Analytics, The University of Sydney Business School, The University of Sydney, Sydney, NSW, Australia
Homepage
same name
  • Junbin Gao — 27 papers, h 27
  • Junbin Gao — 15 papers
  • Junbin Gao — 2 papers
  • Junbin Gao — 1 paper, h 3
  • Junbin Gao — 1 paper

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
20152019
most citedMulti-View Spectral Clustering via Structured Low-Rank Matrix Factorization

433 citations · 821 across the 11 of their papers we have counts for

collaborators
Showing 2015Show all

4 papers · 1 filter

cs.CV2015

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization

Yanfeng Sun, Junbin Gao, Xia Hong +2

Tensors or multiarray data are generalizations of matrices. Tensor clustering has become a very important research topic due to the intrinsically rich structures in real-world mult…

cs.CV2015★ 5 cited

Segmentation of Subspaces in Sequential Data

Stephen Tierney, Yi Guo, Junbin Gao

We propose Ordered Subspace Clustering (OSC) to segment data drawn from a sequentially ordered union of subspaces. Similar to Sparse Subspace Clustering (SSC) we formulate the prob…

cs.CV2015★ 10 cited

Low Rank Representation on Grassmann Manifolds: An Extrinsic Perspective

Boyue Wang, Yongli Hu, Junbin Gao +2

Many computer vision algorithms employ subspace models to represent data. The Low-rank representation (LRR) has been successfully applied in subspace clustering for which data are…

cs.CV2015★ 6 cited

Kernelized Low Rank Representation on Grassmann Manifolds

Boyue Wang, Yongli Hu, Junbin Gao +2

Low rank representation (LRR) has recently attracted great interest due to its pleasing efficacy in exploring low-dimensional subspace structures embedded in data. One of its succe…

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