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Chunfeng Cui

4 papers hereh-index 6141 citations12 works total

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

author position
  • first author1
  • middle author1
  • last author2

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

fields
  • math.OC2
  • cs.LG1
  • cs.RO1
same name
  • Chunfeng Cui — 28 papers, h 9
  • Chunfeng Cui — 13 papers, h 4
  • Chunfeng Cui — 8 papers, h 7
  • Chunfeng Cui — 2 papers, h 3
  • Chunfeng Cui — 1 paper, h 7
  • Chunfeng Cui — 1 paper, h 2

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
20172023
most citedOptimization Models and Interpretations for Three Types of Adversarial Perturbations against Support Vector Machines

1 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2023★ 1 cited

Augmented Quaternion and Augmented Unit Quaternion Optimization

Liqun Qi, Xiangke Wang, Chunfeng Cui

In this paper, we introduce and explore augmented quaternions and augmented unit quaternions, and present an augmented unit quaternion optimization model. An augmented quaternion c…

math.OC2023

Improving the generalization via coupled tensor norm regularization

Ying Gao, Yunfei Qu, Chunfeng Cui +1

In this paper, we propose a coupled tensor norm regularization that could enable the model output feature and the data input to lie in a low-dimensional manifold, which helps us to…

cs.LG2022★ 1 cited

Optimization Models and Interpretations for Three Types of Adversarial Perturbations against Support Vector Machines

Wen Su, Qingna Li, Chunfeng Cui

Adversarial perturbations have drawn great attentions in various deep neural networks. Most of them are computed by iterations and cannot be interpreted very well. In contrast, lit…

math.OC2017

A Quadratic Penalty Method for Hypergraph Matching

Chunfeng Cui, Qingna Li, Liqun Qi +1

Hypergraph matching is a fundamental problem in computer vision. Mathematically speaking, it maximizes a polynomial objective function, subject to assignment constraints. In this p…

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