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Unsupervised feature selection by regularized self-representation

https://doi.org/10.1016/j.patcog.2014.08.006
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.patcog.2007.10.009openalex-snapshot
Constraint Score: A new filter method for feature selection with pairwise constraints
inferredcites →https://doi.org/10.1016/j.patcog.2008.03.007openalex-snapshot
Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm
inferredcites →https://doi.org/10.1016/j.patcog.2010.10.006openalex-snapshot
A unifying criterion for unsupervised clustering and feature selection
inferredcites →https://doi.org/10.1080/10618600.2000.10474858openalex-snapshot
Optimization Transfer Using Surrogate Objective Functions
inferredcites →https://doi.org/10.1109/34.990133openalex-snapshot
Unsupervised feature selection using feature similarity
inferredcites →https://doi.org/10.1109/cvpr.2005.38openalex-snapshot
A Non-Local Algorithm for Image Denoising
inferredcites →https://doi.org/10.1109/cvpr.2009.5206547openalex-snapshot
Sparse subspace clustering
inferredcites →https://doi.org/10.1109/cvpr.2010.5539967openalex-snapshot
Visual classification with multi-task joint sparse representation
inferredcites →https://doi.org/10.1109/cvpr.2012.6247966openalex-snapshot
l2, 1 Regularized correntropy for robust feature selection
inferredcites →https://doi.org/10.1109/cvprw.2009.5206547openalex-snapshot
Sparse subspace clustering
inferredcites →https://doi.org/10.1109/tip.2007.911828openalex-snapshot
Sparse Representation for Color Image Restoration
inferredcites →https://doi.org/10.1109/tkde.2011.222openalex-snapshot
On Similarity Preserving Feature Selection
inferredcites →https://doi.org/10.1109/tpami.2003.1182100openalex-snapshot
Unsupervised feature selection applied to content-based retrieval of lung images
inferredcites →https://doi.org/10.1109/tpami.2008.79openalex-snapshot
Robust Face Recognition via Sparse Representation
inferredcites →https://doi.org/10.1126/science.156.3775.636openalex-snapshot
How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension
inferredcites →https://doi.org/10.1145/1015330.1015435openalex-snapshot
Feature selection, L 1 vs. L 2 regularization, and rotational invariance
inferredcites →https://doi.org/10.1145/1273496.1273641openalex-snapshot
Spectral feature selection for supervised and unsupervised learning
inferredcites →https://doi.org/10.1145/1835804.1835848openalex-snapshot
Unsupervised feature selection for multi-cluster data
inferredcites →https://doi.org/10.1145/2339530.2339673openalex-snapshot
Unsupervised feature selection for linked social media data
inferredcites →https://doi.org/10.1515/9781400830213openalex-snapshot
The Econometrics of Financial Markets
inferredcites →https://doi.org/10.1609/aaai.v24i1.7671openalex-snapshot
Efficient Spectral Feature Selection with Minimum Redundancy
inferredcites →https://doi.org/10.1609/aaai.v26i1.8289openalex-snapshot
Unsupervised Feature Selection Using Nonnegative Spectral Analysis
inferredcites →https://doi.org/10.2307/j.ctt7skm5openalex-snapshot
The Econometrics of Financial Markets
inferredcites →https://doi.org/10.5555/1005332.1016787openalex-snapshot
Feature Selection for Unsupervised Learning
inferredcites →https://doi.org/10.5555/944919.944968openalex-snapshot
An introduction to variable and feature selection
inferredcites →https://doi.org/10.5591/978-1-57735-516-8/ijcai11-267openalex-snapshot
l 2,1 -norm regularized discriminative feature selection for unsupervised learning
inferredcites →https://doi.org/10.7551/mitpress/7503.003.0010openalex-snapshot
Multi-Task Feature Learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A New Multi‐Objective Binary Bat Algorithm for Feature Selection in Intrusion Detection Systems
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Joint L2,1 Norm and Fisher Discrimination Constrained Feature Selection for Rational Synthesis of Microporous Aluminophosphates
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Spectral Band Selection Using Binary Gray Wolf Optimizer and Signal to Noise Ration Measure
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Differentiable Feature Selection, A Reparameterization Approach
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Deep Feature selection
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Non-convex Regularized Self-representation for Unsupervised Feature Selection
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A Differential Evolution Approach to Feature Selection and Instance Selection
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Unsupervised Feature Selection with Graph Regularized Nonnegative Self-representation
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Joint Discriminative and Representative Feature Selection for Alzheimer’s Disease Diagnosis
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Unsupervised Hypergraph Feature Selection with Low-Rank and Self-Representation Constraints
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Supervised Feature Selection by Robust Sparse Reduced-Rank Regression
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Adaptive Graph Learning for Supervised Low-Rank Spectral Feature Selection
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Feature selection using class-level regularized self-representation
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Joint learning of graph and latent representation for unsupervised feature selection
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Unsupervised attribute reduction based on neighborhood dependency
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Robust unsupervised feature selection based on matrix factorization with adaptive loss via bi-stochastic graph regularization
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Block-diagonal graph embedding for unsupervised feature selection
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An intelligent technique for pattern-based clustering of continuous-valued datasets
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Low-rank unsupervised graph feature selection via feature self-representation
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Leverage triple relational structures via low-rank feature reduction for multi-output regression
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Low-rank feature selection for multi-view regression
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Double sparse-representation feature selection algorithm for classification
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Unsupervised feature selection with graph learning via low-rank constraint
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Hypergraph expressing low-rank feature selection algorithm
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Dynamic graph learning for spectral feature selection
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Unsupervised feature selection via local structure learning and sparse learning
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Robust inner product regularized unsupervised feature selection
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Unsupervised feature selection based on local structure learning
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Nonnegative spectral clustering and adaptive graph-based matrix regression for unsupervised image feature selection
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Joint Spectral Clustering based on Optimal Graph and Feature Selection
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Comparisons of filter, wrapper, and embedded feature selection for rockfall susceptibility prediction and mapping
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A new algorithm for solving a class of matrix optimization problem arising in unsupervised feature selection
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Joint self-representation and subspace learning for unsupervised feature selection
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Low-rank hypergraph feature selection for multi-output regression
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Unsupervised feature selection via multiple graph fusion and feature weight learning
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FSCAM: CAM-Based Feature Selection for Clustering scRNA-seq
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Multi-label feature selection via feature manifold learning and sparsity regularization
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Unsupervised feature selection based on self-representation sparse regression and local similarity preserving
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Self-representation nearest neighbor search for classification
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Local and global regularized sparse coding for data representation
inferred← citeshttps://doi.org/10.1016/j.neucom.2015.11.001openalex-snapshot
Cluster structure preserving unsupervised feature selection for multi-view tasks
inferred← citeshttps://doi.org/10.1016/j.neucom.2016.09.043openalex-snapshot
Unsupervised feature selection via Diversity-induced Self-representation
inferred← citeshttps://doi.org/10.1016/j.neucom.2016.10.087openalex-snapshot
Feature self-representation based hypergraph unsupervised feature selection via low-rank representation
inferred← citeshttps://doi.org/10.1016/j.neucom.2016.11.076openalex-snapshot
Self-representation dimensionality reduction for multi-model classification
inferred← citeshttps://doi.org/10.1016/j.neucom.2017.02.034openalex-snapshot
Robust unsupervised feature selection via matrix factorization
inferred← citeshttps://doi.org/10.1016/j.neucom.2017.08.047openalex-snapshot
Unsupervised feature selection by regularized matrix factorization
inferred← citeshttps://doi.org/10.1016/j.neucom.2017.11.061openalex-snapshot
Co-regularized unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2018.02.032openalex-snapshot
Distribution preserving learning for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2018.04.001openalex-snapshot
Structure preserving unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2018.05.117openalex-snapshot
Graph autoencoder-based unsupervised feature selection with broad and local data structure preservation
inferred← citeshttps://doi.org/10.1016/j.neucom.2018.06.010openalex-snapshot
Low-rank structure preserving for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2018.11.060openalex-snapshot
Dual graph regularized compact feature representation for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.10.018openalex-snapshot
Unsupervised feature selection via adaptive hypergraph regularized latent representation learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.12.017openalex-snapshot
Deep feature selection using a teacher-student network
inferred← citeshttps://doi.org/10.1016/j.neucom.2022.03.004openalex-snapshot
Robust dual-graph regularized and minimum redundancy based on self-representation for semi-supervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2022.10.030openalex-snapshot
Unsupervised feature selection guided by orthogonal representation of feature space
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.126458openalex-snapshot
Multi-view intuitionistic fuzzy support vector machines with insensitive pinball loss for classification of noisy data
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128202openalex-snapshot
Differentiable gated autoencoders for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.129557openalex-snapshot
Bilinear Self-Representation for Unsupervised Feature Selection with Structure Learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2026.133609openalex-snapshot
UAMOD: Unsupervised feature selection algorithm using adaptive multi-neighborhood fuzzy entropy for outlier detection
inferred← citeshttps://doi.org/10.1016/j.neucom.2026.133928openalex-snapshot
Joint sample-feature subspace learning via bidirectional reconstruction for feature selection
inferred← citeshttps://doi.org/10.1016/j.neunet.2015.06.001openalex-snapshot
Locality preserving score for joint feature weights learning
inferred← citeshttps://doi.org/10.1016/j.neunet.2018.01.014openalex-snapshot
Accelerated low-rank representation for subspace clustering and semi-supervised classification on large-scale data
inferred← citeshttps://doi.org/10.1016/j.neunet.2019.04.015openalex-snapshot
Unsupervised feature selection via latent representation learning and manifold regularization
inferred← citeshttps://doi.org/10.1016/j.neunet.2022.03.004openalex-snapshot
Unsupervised feature selection via adaptive autoencoder with redundancy control
inferred← citeshttps://doi.org/10.1016/j.neunet.2022.04.002openalex-snapshot
Deep unsupervised feature selection by discarding nuisance and correlated features
inferred← citeshttps://doi.org/10.1016/j.neunet.2022.06.016openalex-snapshot
Graph regularized spatial–spectral subspace clustering for hyperspectral band selection
inferred← citeshttps://doi.org/10.1016/j.neunet.2023.10.037openalex-snapshot
Maximum margin and global criterion based-recursive feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2015.12.008openalex-snapshot
Global and local structure preserving sparse subspace learning: An iterative approach to unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2016.08.011openalex-snapshot
An efficient semi-supervised representatives feature selection algorithm based on information theory
inferred← citeshttps://doi.org/10.1016/j.patcog.2017.11.006openalex-snapshot
Manifold constraint transfer for visual structure-driven optimization
inferred← citeshttps://doi.org/10.1016/j.patcog.2018.05.012openalex-snapshot
A Kernel Partial least square based feature selection method
inferred← citeshttps://doi.org/10.1016/j.patcog.2018.07.021openalex-snapshot
Online multi-label streaming feature selection based on neighborhood rough set
inferred← citeshttps://doi.org/10.1016/j.patcog.2019.01.014openalex-snapshot
Joint sparse matrix regression and nonnegative spectral analysis for two-dimensional unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2019.04.020openalex-snapshot
Nonnegative Laplacian embedding guided subspace learning for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2019.05.009openalex-snapshot
Cross-domain network representations
inferred← citeshttps://doi.org/10.1016/j.patcog.2020.107375openalex-snapshot
Unsupervised feature selection with adaptive multiple graph learning
inferred← citeshttps://doi.org/10.1016/j.patcog.2020.107663openalex-snapshot
Pairwise dependence-based unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2020.107742openalex-snapshot
Joint adaptive manifold and embedding learning for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2021.107987openalex-snapshot
SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning
inferred← citeshttps://doi.org/10.1016/j.patcog.2021.108299openalex-snapshot
Graph regularized locally linear embedding for unsupervised feature selection
inferred← citeshttps://doi.org/10.1016/j.patcog.2022.108622openalex-snapshot
Unsupervised feature selection via adaptive graph and dependency score
inferred← citeshttps://doi.org/10.1016/j.patcog.2023.109676openalex-snapshot
Robust unsupervised feature selection via data relationship learning
inferred← citeshttps://doi.org/10.1016/j.patcog.2023.110183openalex-snapshot
Unsupervised feature selection by learning exponential weights
inferred← citeshttps://doi.org/10.1016/j.patcog.2025.112728openalex-snapshot
Multi-view unsupervised feature selection with unified measurement of consistency and diversity
inferred← citeshttps://doi.org/10.1016/j.patrec.2017.09.022openalex-snapshot
Unsupervised feature selection by combining subspace learning with feature self-representation
inferred← citeshttps://doi.org/10.1016/j.patrec.2018.06.029openalex-snapshot
Unsupervised feature selection by self-paced learning regularization
inferred← citeshttps://doi.org/10.1016/j.patrec.2018.08.029openalex-snapshot
Supervised feature selection by self-paced learning regression
inferred← citeshttps://doi.org/10.1016/j.procs.2023.08.129openalex-snapshot
Sparse regularization based feature selection: A survey
inferred← citeshttps://doi.org/10.1016/j.procs.2025.04.357openalex-snapshot
Entropy Dependency-based Unsupervised Feature Selection
inferred← citeshttps://doi.org/10.1049/iet-cvi.2016.0287openalex-snapshot
Compact discriminative object representation via weakly supervised learning for real‐time visual tracking
inferred← citeshttps://doi.org/10.1049/ipr2.12828openalex-snapshot
Latent low‐rank representation sparse regression model with symmetric constraint for unsupervised feature selection
inferred← citeshttps://doi.org/10.1080/00949655.2020.1822358openalex-snapshot
A novel feature selection approach based on clustering algorithm
inferred← citeshttps://doi.org/10.1080/01431161.2024.2305180openalex-snapshot
Multigraph approximate-representation learning for hyperspectral band selection
inferred← citeshttps://doi.org/10.1080/23799927.2017.1330283openalex-snapshot
Unsupervised feature selection with the largest angle coding
inferred← citeshttps://doi.org/10.1088/1361-6501/abfb1fopenalex-snapshot
Ensemble clustering-based fault diagnosis method incorporating traditional and deep representation features
inferred← citeshttps://doi.org/10.1108/imds-11-2016-0491openalex-snapshot
A high-dimensional classification approach based on class-dependent feature subspace
inferred← citeshttps://doi.org/10.1109/access.2017.2699741openalex-snapshot
Structure Preserving Non-negative Feature Self-Representation for Unsupervised Feature Selection
inferred← citeshttps://doi.org/10.1109/access.2017.2724763openalex-snapshot
Inner Product Regularized Nonnegative Self Representation for Image Classification and Clustering
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