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Adaptive density peak clustering based on K-nearest neighbors with aggregating strategy

Knowledge-based systems, 2017-10, Vol.133, p.208-220

2017

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LE & LLE Regularized Nonnegative Tucker Decomposition for clustering of high dimensional datasets

Neurocomputing (Amsterdam), 2019-10, Vol.364, p.77-94

2019

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High order discriminant analysis based on Riemannian optimization

Knowledge-based systems, 2020-05, Vol.195, p.105630, Article 105630

2020

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Regularized constraint subspace based method for image set classification

Pattern recognition, 2018-04, Vol.76, p.434-448

2018

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Tensor local linear embedding with global subspace projection optimisation

IET computer vision, 2022-04, Vol.16 (3), p.241-254

2022

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Tensor dimensionality reduction via mode product and HSIC

IET image processing, 2021-10, Vol.15 (12), p.2986-3002

2021

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Local tangent space alignment based on Hilbert–Schmidt independence criterion regularization

Pattern analysis and applications : PAA, 2020-05, Vol.23 (2), p.855-868

2020

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Domain adaption based on source dictionary regularized RKHS subspace learning

Pattern analysis and applications : PAA, 2021-11, Vol.24 (4), p.1513-1532

2021

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RKHS subspace domain adaption via minimum distribution gap

Pattern analysis and applications : PAA, 2023-08, Vol.26 (3), p.1425-1439

2023

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Dimensionality Reduction Based on kCCC and Manifold Learning

Journal of mathematical imaging and vision, 2021-10, Vol.63 (8), p.1010-1035

2021

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Dimensionality Reduction of SPD Data Based on Riemannian Manifold Tangent Spaces and Isometry

Entropy (Basel, Switzerland), 2021-08, Vol.23 (9), p.1117

2021

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Dimensionality reduction based on multi-local linear regression and global subspace projection distance minimum

Pattern analysis and applications : PAA, 2021-11, Vol.24 (4), p.1713-1730

2021

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The framework of learnable kernel function and its application to dictionary learning of SPD data

Pattern analysis and applications : PAA, 2021-05, Vol.24 (2), p.723-739

2021

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Local Coordinates Alignment With Global Preservation for Dimensionality Reduction

IEEE transaction on neural networks and learning systems, 2013-01, Vol.24 (1), p.106-117

2013

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A Framework for Short Video Recognition Based on Motion Estimation and Feature Curves on SPD Manifolds

Applied sciences, 2022-05, Vol.12 (9), p.4669

2022

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Domain Adaption Based on MSE Criterion and Progressive RKHS Subspace Learning (MSEpRKHSDA)

IEEE access, 2022, Vol.10, p.1-1

2022

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Dictionary Learning of Symmetric Positive Definite Data Based on Riemannian Manifold Tangent Spaces and Local Homeomorphism

IEEE access, 2022, Vol.10, p.46114-46127

2022

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Regularized RKHS-Based Subspace Learning for Motor Imagery Classification

Entropy (Basel, Switzerland), 2022-01, Vol.24 (2), p.195

2022

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EEG Mental Recognition Based on RKHS Learning and Source Dictionary Regularized RKHS Subspace Learning

IEEE access, 2021, Vol.9, p.150545-150559

2021

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SPD Data Dictionary Learning Based on Kernel Learning and Riemannian Metric

IEEE access, 2020, Vol.8, p.61956-61972

2020

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Domain Adaption Based on Symmetric Matrices Space Bi-Subspace Learning and Source Linear Discriminant Analysis Regularization

IEEE access, 2021, Vol.9, p.146984-147002

2021

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Face recognition based on the fusion of global and local HOG features of face images

IET computer vision, 2014-06, Vol.8 (3), p.224-234

2014

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Grassmann manifold for nearest points image set classification

Pattern recognition letters, 2015-12, Vol.68, p.190-196

2015

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Dimensionality Reduction of Tensors Based on Local Homeomorphism and Global Subspace Projection Distance Minimum

IEEE access, 2020, Vol.8, p.116064-116077

2020

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A Double-Density Clustering Method Based on “Nearest to First in” Strategy

Symmetry (Basel), 2020-05, Vol.12 (5), p.747

2020

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Adaptive density peak clustering based on K-nearest neighbors with aggregating strategy

LE & LLE Regularized Nonnegative Tucker Decomposition for clustering of high dimensional datasets

High order discriminant analysis based on Riemannian optimization

Regularized constraint subspace based method for image set classification

Tensor local linear embedding with global subspace projection optimisation

Tensor dimensionality reduction via mode product and HSIC

Local tangent space alignment based on Hilbert–Schmidt independence criterion regularization

Domain adaption based on source dictionary regularized RKHS subspace learning

RKHS subspace domain adaption via minimum distribution gap

Dimensionality Reduction Based on kCCC and Manifold Learning

Dimensionality Reduction of SPD Data Based on Riemannian Manifold Tangent Spaces and Isometry

Dimensionality reduction based on multi-local linear regression and global subspace projection distance minimum

The framework of learnable kernel function and its application to dictionary learning of SPD data

Local Coordinates Alignment With Global Preservation for Dimensionality Reduction

A Framework for Short Video Recognition Based on Motion Estimation and Feature Curves on SPD Manifolds

Domain Adaption Based on MSE Criterion and Progressive RKHS Subspace Learning (MSEpRKHSDA)

Dictionary Learning of Symmetric Positive Definite Data Based on Riemannian Manifold Tangent Spaces and Local Homeomorphism

Regularized RKHS-Based Subspace Learning for Motor Imagery Classification

EEG Mental Recognition Based on RKHS Learning and Source Dictionary Regularized RKHS Subspace Learning

SPD Data Dictionary Learning Based on Kernel Learning and Riemannian Metric

Domain Adaption Based on Symmetric Matrices Space Bi-Subspace Learning and Source Linear Discriminant Analysis Regularization

Face recognition based on the fusion of global and local HOG features of face images

Grassmann manifold for nearest points image set classification

Dimensionality Reduction of Tensors Based on Local Homeomorphism and Global Subspace Projection Distance Minimum

A Double-Density Clustering Method Based on “Nearest to First in” Strategy

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