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One-step spectral rotation clustering with balanced constrains

World wide web (Bussum), 2022, Vol.25 (1), p.259-280

2022

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Feature self-representation based hypergraph unsupervised feature selection via low-rank representation

Neurocomputing (Amsterdam), 2017-08, Vol.253, p.127-134

2017

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Robust self-tuning spectral clustering

Neurocomputing (Amsterdam), 2020-05, Vol.391, p.243-248

Wen, Guoqiu

2020

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Spectral clustering algorithm combining local covariance matrix with normalization

Neural computing & applications, 2020-06, Vol.32 (11), p.6611-6618

2020

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Sparse Nonlinear Feature Selection Algorithm via Local Structure Learning

Emerging science journal, 2019-04, Vol.3 (2), p.115-129

2019

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Unsupervised feature selection by self-paced learning regularization

Pattern recognition letters, 2020-04, Vol.132, p.4-11

2020

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Dynamic graph convolutional networks by semi-supervised contrastive learning

Pattern recognition, 2023-07, Vol.139, p.109486, Article 109486

2023

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An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster–Shafer theory of evidence: An application in medical diagnosis

Artificial intelligence in medicine, 2015-07, Vol.64 (3), p.161-171

2015

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Self-paced Learning for K-means Clustering Algorithm

Pattern recognition letters, 2020-04, Vol.132, p.69-75

2020

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Supervised feature selection by self-paced learning regression

Pattern recognition letters, 2020-04, Vol.132, p.30-37

2020

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Spectral representation learning for one-step spectral rotation clustering

Neurocomputing (Amsterdam), 2020-09, Vol.406, p.361-370

2020

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Soft coverings and their parameter reductions

Applied soft computing, 2015-06, Vol.31, p.48-60

2015

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One-step spectral clustering based on self-paced learning

Pattern recognition letters, 2020-07, Vol.135, p.8-14

2020

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Noise-resistant graph neural networks with manifold consistency and label consistency

Expert systems with applications, 2024-07, Vol.245, p.123120, Article 123120

2024

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One-step spectral rotation clustering for imbalanced high-dimensional data

Information processing & management, 2021-01, Vol.58 (1), p.102388, Article 102388

2021

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A novel low-rank hypergraph feature selection for multi-view classification

Neurocomputing (Amsterdam), 2017-08, Vol.253, p.115-121

2017

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Adaptive structure learning for low-rank supervised feature selection

Pattern recognition letters, 2018-07, Vol.109, p.89-96

2018

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Exclusive feature selection and multi-view learning for Alzheimer’s Disease

Journal of visual communication and image representation, 2019-10, Vol.64, p.102605, Article 102605

2019

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Global and Local Structure Preservation for Nonlinear High-dimensional Spectral Clustering

Computer journal, 2021-08, Vol.64 (7), p.993-1004

2021

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Multi-scale graph classification with shared graph neural network

World wide web (Bussum), 2023-05, Vol.26 (3), p.949-966

2023

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A Method for Fuzzy Soft Sets in Decision Making Based on Grey Relational Analysis and D-S Theory of Evidence : Application to Medical Diagnosis

Computational and mathematical methods in medicine, 2014-01, Vol.2014 (2014), p.1-12

2014

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A Temporal Knowledge Graph Embedding Model Based on Variable Translation

Tsinghua science and technology, 2024-10, Vol.29 (5), p.1554-1565

2024

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An Efficient Algorithm Combining Spectral Clustering with Feature Selection

Neural processing letters, 2020-12, Vol.52 (3), p.1913-1925

2020

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Sparse Low-Rank and Graph Structure Learning for Supervised Feature Selection

Neural processing letters, 2020-12, Vol.52 (3), p.1793-1809

2020

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Using Locality Preserving Projections to Improve the Performance of Kernel Clustering

Neural processing letters, 2020-12, Vol.52 (3), p.1827-1842

2020

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One-step spectral rotation clustering with balanced constrains

Feature self-representation based hypergraph unsupervised feature selection via low-rank representation

Robust self-tuning spectral clustering

Spectral clustering algorithm combining local covariance matrix with normalization

Sparse Nonlinear Feature Selection Algorithm via Local Structure Learning

Unsupervised feature selection by self-paced learning regularization

Dynamic graph convolutional networks by semi-supervised contrastive learning

An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster–Shafer theory of evidence: An application in medical diagnosis

Self-paced Learning for K-means Clustering Algorithm

Supervised feature selection by self-paced learning regression

Spectral representation learning for one-step spectral rotation clustering

Soft coverings and their parameter reductions

One-step spectral clustering based on self-paced learning

Noise-resistant graph neural networks with manifold consistency and label consistency

One-step spectral rotation clustering for imbalanced high-dimensional data

A novel low-rank hypergraph feature selection for multi-view classification

Adaptive structure learning for low-rank supervised feature selection

Exclusive feature selection and multi-view learning for Alzheimer’s Disease

Global and Local Structure Preservation for Nonlinear High-dimensional Spectral Clustering

Multi-scale graph classification with shared graph neural network

A Method for Fuzzy Soft Sets in Decision Making Based on Grey Relational Analysis and D-S Theory of Evidence : Application to Medical Diagnosis

A Temporal Knowledge Graph Embedding Model Based on Variable Translation

An Efficient Algorithm Combining Spectral Clustering with Feature Selection

Sparse Low-Rank and Graph Structure Learning for Supervised Feature Selection

Using Locality Preserving Projections to Improve the Performance of Kernel Clustering

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