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Self-weighted Multi-view Fuzzy Clustering

https://doi.org/10.1145/3396238
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Iteratively reweighted least squares minimization for sparse recovery
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Pattern Recognition of Surface EMG Biological Signals by Means of Hilbert Spectrum and Fuzzy Clustering
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Spectral clustering via half-quadratic optimization
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Robust SVM with adaptive graph learning
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Fuzzy c-means clustering with weighted image patch for image segmentation
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Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
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Multi-view fuzzy clustering with minimax optimization for effective clustering of data from multiple sources
inferredcites →https://doi.org/10.1016/j.inffus.2017.02.007openalex-snapshot
Multi-view learning overview: Recent progress and new challenges
inferredcites →https://doi.org/10.1016/j.jss.2011.12.020openalex-snapshot
Strong fuzzy c-means in medical image data analysis
inferredcites →https://doi.org/10.1016/j.patcog.2019.107175openalex-snapshot
Spectral rotation for deep one-step clustering
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Unsupervised feature selection by self-paced learning regularization
inferredcites →https://doi.org/10.1080/01969727308546046openalex-snapshot
A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
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Protein network inference from multiple genomic data: a supervised approach
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A validity measure for fuzzy clustering
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Diversity-induced Multi-view Subspace Clustering
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Proceedings of 1995 IEEE International Conference on Fuzzy Systems.
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Iteratively reweighted algorithms for compressive sensing
inferredcites →https://doi.org/10.1109/icdm.2004.10095openalex-snapshot
Multi-View Clustering
inferredcites →https://doi.org/10.1109/icdm.2009.138openalex-snapshot
CoFKM: A Centralized Method for Multiple-View Clustering
inferredcites →https://doi.org/10.1109/icmlc.2004.1378168openalex-snapshot
Proceedings of 2004 International Conference on Machine Learning and Cybernetics
inferredcites →https://doi.org/10.1109/jstsp.2019.2957952openalex-snapshot
Video Coding Optimization for Virtual Reality 360-Degree Source
inferredcites →https://doi.org/10.1109/tcyb.2014.2334595openalex-snapshot
Collaborative Fuzzy Clustering From Multiple Weighted Views
inferredcites →https://doi.org/10.1109/tcyb.2018.2883970openalex-snapshot
Graph Convolutional Network Hashing
inferredcites →https://doi.org/10.1109/tip.2015.2405340openalex-snapshot
Hashing on Nonlinear Manifolds
inferredcites →https://doi.org/10.1109/tkde.2018.2858782openalex-snapshot
Low-Rank Sparse Subspace for Spectral Clustering
inferredcites →https://doi.org/10.1109/tkde.2018.2873378openalex-snapshot
One-Step Multi-View Spectral Clustering
inferredcites →https://doi.org/10.1109/tkde.2019.2956530openalex-snapshot
Efficient Utilization of Missing Data in Cost-Sensitive Learning
inferredcites →https://doi.org/10.1109/tkde.2020.2970050openalex-snapshot
Exploiting Subspace Relation in Semantic Labels for Cross-Modal Hashing
inferredcites →https://doi.org/10.1109/tmm.2017.2703636openalex-snapshot
Graph PCA Hashing for Similarity Search
inferredcites →https://doi.org/10.1109/tnn.2005.845141openalex-snapshot
Survey of Clustering Algorithms
inferredcites →https://doi.org/10.1109/tnnls.2017.2673241openalex-snapshot
Efficient kNN Classification With Different Numbers of Nearest Neighbors
inferredcites →https://doi.org/10.1109/tnnls.2018.2851077openalex-snapshot
From Deterministic to Generative: Multimodal Stochastic RNNs for Video Captioning
inferredcites →https://doi.org/10.1126/science.290.5500.2323openalex-snapshot
Nonlinear Dimensionality Reduction by Locally Linear Embedding
inferredcites →https://doi.org/10.1142/s0219720005001375openalex-snapshot
NOISE-ROBUST SOFT CLUSTERING OF GENE EXPRESSION TIME-COURSE DATA
inferredcites →https://doi.org/10.1145/1390156.1390191openalex-snapshot
Efficient projections onto the l 1 -ball for learning in high dimensions
inferredcites →https://doi.org/10.1145/1497577.1497578openalex-snapshot
Clustering high-dimensional data
inferredcites →https://doi.org/10.1145/1553374.1553391openalex-snapshot
Multi-view clustering via canonical correlation analysis
inferredcites →https://doi.org/10.5555/3288251.3288293openalex-snapshot
Unsupervised feature selection via local structure learning and sparse learning

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-032-29319-0_12openalex-snapshot
Optimizing Fuzzy Clustering Algorithms Through Multi Objective Approaches: Improving Accuracy, Validity and Computational Efficiency
inferred← citeshttps://doi.org/10.1007/978-981-97-7679-5_6openalex-snapshot
Multi-view Data Clustering Through Consensus Graph and Data Representation Learning
inferred← citeshttps://doi.org/10.1007/s00371-025-04283-zopenalex-snapshot
Enhancing deep fuzzy K-means clustering with pseudo-category features: a novel approach
inferred← citeshttps://doi.org/10.1007/s00521-020-05431-3openalex-snapshot
Modified semi-supervised affinity propagation clustering with fuzzy density fruit fly optimization
inferred← citeshttps://doi.org/10.1007/s11063-020-10297-6openalex-snapshot
An Efficient Algorithm Combining Spectral Clustering with Feature Selection
inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105541openalex-snapshot
Robust and fuzzy ensemble framework via spectral learning for random projection-based fuzzy-c-means clustering
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.107857openalex-snapshot
Breaking down multi-view clustering: A comprehensive review of multi-view approaches for complex data structures
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111429openalex-snapshot
Heart failure disease stratification with temporal electronic health records: Patient representation and sub-phenotypes identification
inferred← citeshttps://doi.org/10.1016/j.inffus.2023.101917openalex-snapshot
Neighbor group structure preserving based consensus graph learning for incomplete multi-view clustering
inferred← citeshttps://doi.org/10.1016/j.inffus.2023.102025openalex-snapshot
Latent information-guided one-step multi-view fuzzy clustering based on cross-view anchor graph
inferred← citeshttps://doi.org/10.1016/j.ins.2022.01.017openalex-snapshot
One-step multi-view spectral clustering with cluster label correlation graph
inferred← citeshttps://doi.org/10.1016/j.ins.2023.119366openalex-snapshot
Single phase multi-view clustering using unified graph learning and spectral representation
inferred← citeshttps://doi.org/10.1016/j.ins.2024.120830openalex-snapshot
Discriminative embedded multi-view fuzzy C-means clustering for feature-redundant and incomplete data
inferred← citeshttps://doi.org/10.1016/j.neucom.2022.12.023openalex-snapshot
One step multi-view spectral clustering via joint adaptive graph learning and matrix factorization
inferred← citeshttps://doi.org/10.1016/j.neunet.2024.106197openalex-snapshot
Towards a unified framework for graph-based multi-view clustering
inferred← citeshttps://doi.org/10.1016/j.neunet.2025.107652openalex-snapshot
Incomplete multi-view clustering via efficient anchor tensor recovery framework
inferred← citeshttps://doi.org/10.1016/j.patcog.2021.108429openalex-snapshot
Self-weighting multi-view spectral clustering based on nuclear norm
inferred← citeshttps://doi.org/10.1080/01431161.2021.1934595openalex-snapshot
A semi-supervised learning method for hyperspectral imagery based on self-training and local-based affinity propagation
inferred← citeshttps://doi.org/10.1109/icces51350.2021.9489139openalex-snapshot
Fuzzy Information Mining for Four-dimensional Core Values of Micro Entrepreneurs based on Internet Data Understanding
inferred← citeshttps://doi.org/10.1109/iske54062.2021.9755423openalex-snapshot
A Robust Method for Simultaneous Unsupervised Feature Selection and Clustering
inferred← citeshttps://doi.org/10.1109/tai.2021.3116546openalex-snapshot
ANIMC: A Soft Approach for Autoweighted Noisy and Incomplete Multiview Clustering
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An End-to-End Approach for Graph-Based Multi-View Data Clustering
inferred← citeshttps://doi.org/10.1109/tetci.2025.3619520openalex-snapshot
Adaptive Multi-View Fuzzy Clustering With Diverse Anchor Based Guidance
inferred← citeshttps://doi.org/10.1109/tfuzz.2022.3164796openalex-snapshot
Enhanced Multiview Fuzzy Clustering Using Double Visible-Hidden View Cooperation and Network LASSO Constraint
inferred← citeshttps://doi.org/10.1109/tfuzz.2022.3203506openalex-snapshot
End-to-End Incomplete Multiview Fuzzy Clustering With Adaptive Missing View Imputation and Cooperative Learning
inferred← citeshttps://doi.org/10.1109/tfuzz.2023.3335361openalex-snapshot
An Efficient Federated Multiview Fuzzy C-Means Clustering Method
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High-order Topology for Deep Single-Cell Multiview Fuzzy Clustering
inferred← citeshttps://doi.org/10.1109/tfuzz.2024.3489025openalex-snapshot
Dual Anchor Graph Fuzzy Clustering for Multiview Data
inferred← citeshttps://doi.org/10.1109/tfuzz.2024.3491300openalex-snapshot
Fuzzy Min-Cut With Soft Balancing Effects
inferred← citeshttps://doi.org/10.1109/tfuzz.2025.3650110openalex-snapshot
Parameter-Free Dual-Granularity Weighted Multiview Fuzzy $c$-Means Clustering
inferred← citeshttps://doi.org/10.1109/tfuzz.2026.3651747openalex-snapshot
Enhanced One-Step Incomplete Multiview Fuzzy Clustering With Dual Representation Learning
inferred← citeshttps://doi.org/10.1109/tkde.2021.3078728openalex-snapshot
Fast Multi-view Clustering via Prototype Graph
inferred← citeshttps://doi.org/10.1109/tkde.2022.3231929openalex-snapshot
Multi-View Fuzzy Classification With Subspace Clustering and Information Granules
inferred← citeshttps://doi.org/10.1109/tkde.2023.3248221openalex-snapshot
Multi-View Scholar Clustering With Dynamic Interest Tracking
inferred← citeshttps://doi.org/10.1109/tmm.2024.3521803openalex-snapshot
Graph Proxy Fusion: Consensus Graph Intermediated Multi-View Local Information Fusion Clustering
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Half-Quadratic Minimization for Unsupervised Feature Selection on Incomplete Data
inferred← citeshttps://doi.org/10.1109/tnnls.2021.3056080openalex-snapshot
Fast Self-Supervised Clustering With Anchor Graph
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Low-Rank Graph Completion-Based Incomplete Multiview Clustering
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Scale-Driven Tensor Representation-Based Multiview Clustering
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Consolidating Industrial Small Files Using Robust Graph Clustering
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Fuzzy C-Means Clustering Algorithms with Weighted Membership and Distance
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Sparse Graph Connectivity for Image Segmentation
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One-step Low-Rank Representation for Clustering
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Enhanced Fuzzy Clustering for Incomplete Instance with Evidence Combination
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Privacy-preserving Multi-source Cross-domain Recommendation Based on Knowledge Graph
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Subspace-Contrastive Multi-View Clustering
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Pairwise Constraints Multidimensional Scaling for Discriminative Feature Learning
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Fuzzy Multi-View Learning: Principles, Methodologies, and Future Directions
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