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Grassmannian learning mutual subspace method for image set recognition

Neurocomputing (Amsterdam), 2023-01, Vol.517, p.20-33

2023

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Class mean vector component and discriminant analysis

Pattern recognition letters, 2020-12, Vol.140, p.207-213

Iosifidis, Alexandros

2020

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Task-Dependent and Query-Dependent Subspace Learning for Cross-Modal Retrieval

IEEE access, 2018-01, Vol.6, p.27091-27102

2018

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Guide Subspace Learning for Unsupervised Domain Adaptation

IEEE transaction on neural networks and learning systems, 2020-09, Vol.31 (9), p.3374-3388

2020

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Low-Rank Sparse Subspace for Spectral Clustering

IEEE transactions on knowledge and data engineering, 2019-08, Vol.31 (8), p.1532-1543

2019

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Transfer Learning with Dynamic Distribution Adaptation

ACM transactions on intelligent systems and technology, 2020-02, Vol.11 (1), p.1-25

2020

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CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences

IEEE transactions on geoscience and remote sensing, 2019-07, Vol.57 (7), p.4349-4359

2019

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Locality Preserving Joint Transfer for Domain Adaptation

IEEE transactions on image processing, 2019-12, Vol.28 (12), p.6103-6115

2019

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Label-Embedding for Image Classification

IEEE transactions on pattern analysis and machine intelligence, 2016-07, Vol.38 (7), p.1425-1438

2016

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Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation

IEEE transactions on image processing, 2018-09, Vol.27 (9), p.4260-4273

2018

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Robust Kernelized Multiview Self-Representation for Subspace Clustering

IEEE transaction on neural networks and learning systems, 2021-02, Vol.32 (2), p.868-881

2021

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Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation

IEEE transactions on image processing, 2016-02, Vol.25 (2), p.850-863

2016

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Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval

IEEE transactions on pattern analysis and machine intelligence, 2016-10, Vol.38 (10), p.2010-2023

2016

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Multiple Marginal Fisher Analysis

IEEE transactions on industrial electronics (1982), 2019-12, Vol.66 (12), p.9798-9807

2019

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Adaptive reverse graph learning for robust subspace learning

Information processing & management, 2021-11, Vol.58 (6), p.102733, Article 102733

2021

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Ubiquitously Supervised Subspace Learning

IEEE transactions on image processing, 2009-02, Vol.18 (2), p.241-249

2009

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Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering

Neural networks, 2018-07, Vol.103, p.1-8

2018

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Graph-embedded subspace support vector data description

Pattern recognition, 2023-01, Vol.133, p.108999, Article 108999

2023

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Robust Latent Subspace Learning for Image Classification

IEEE transaction on neural networks and learning systems, 2018-06, Vol.29 (6), p.2502-2515

2018

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Tensor Decomposition for Signal Processing and Machine Learning

IEEE transactions on signal processing, 2017-07, Vol.65 (13), p.3551-3582

2017

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Robust metric learning based on subspace learning with lp−norm

Signal processing, 2022-03, Vol.192, Article 108386

2022

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Generalized Transfer Subspace Learning Through Low-Rank Constraint

International journal of computer vision, 2014-08, Vol.109 (1-2), p.74-93

2014

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PixelHop: A successive subspace learning (SSL) method for object recognition

Journal of visual communication and image representation, 2020-07, Vol.70, p.102749, Article 102749

2020

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Joint and Progressive Subspace Analysis (JPSA) With Spatial-Spectral Manifold Alignment for Semisupervised Hyperspectral Dimensionality Reduction

IEEE transactions on cybernetics, 2021-07, Vol.51 (7), p.3602-3615

2021

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Salient Object Detection via Structured Matrix Decomposition

IEEE transactions on pattern analysis and machine intelligence, 2017-04, Vol.39 (4), p.818-832

2017

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Grassmannian learning mutual subspace method for image set recognition

Class mean vector component and discriminant analysis

Task-Dependent and Query-Dependent Subspace Learning for Cross-Modal Retrieval

Guide Subspace Learning for Unsupervised Domain Adaptation

Low-Rank Sparse Subspace for Spectral Clustering

Transfer Learning with Dynamic Distribution Adaptation

CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences

Locality Preserving Joint Transfer for Domain Adaptation

Label-Embedding for Image Classification

Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation

Robust Kernelized Multiview Self-Representation for Subspace Clustering

Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation

Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval

Multiple Marginal Fisher Analysis

Adaptive reverse graph learning for robust subspace learning

Ubiquitously Supervised Subspace Learning

Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering

Graph-embedded subspace support vector data description

Robust Latent Subspace Learning for Image Classification

Tensor Decomposition for Signal Processing and Machine Learning

Robust metric learning based on subspace learning with lp−norm

Generalized Transfer Subspace Learning Through Low-Rank Constraint

PixelHop: A successive subspace learning (SSL) method for object recognition

Joint and Progressive Subspace Analysis (JPSA) With Spatial-Spectral Manifold Alignment for Semisupervised Hyperspectral Dimensionality Reduction

Salient Object Detection via Structured Matrix Decomposition

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