Learning a consensus affinity matrix for multi-view clustering via subspaces merging on Grassmann manifold

DOI10.1016/j.ins.2020.07.059zbMath1475.62191OpenAlexW3049595097MaRDI QIDQ2056274

Yanyan Li

Publication date: 2 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.07.059

zbMATH Keywords

Grassmann manifoldsparsityalternating direction method of multiplierslow-rankmulti-view clusteringsubspace merging

Mathematics Subject Classification ID

Statistics on manifolds (62R30) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (5)

Adaptive graph guided concept factorization on Grassmann manifold ⋮ Low-rank tensor approximation with local structure for multi-view intrinsic subspace clustering ⋮ On efficient model selection for sparse hard and fuzzy center-based clustering algorithms ⋮ Multi-view clustering by virtually passing mutually supervised smooth messages ⋮ Multi-view clustering with adaptive procrustes on Grassmann manifold

Uses Software

• RCV1

Cites Work

• Unnamed Item
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• On the linear convergence of the alternating direction method of multipliers
• Robust low-rank kernel multi-view subspace clustering based on the Schatten \(p\)-norm and correntropy
• Multi-view cluster analysis with incomplete data to understand treatment effects
• Introduction to Information Retrieval
• The Geometry of Algorithms with Orthogonality Constraints
• Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds
• Convex Sparse Spectral Clustering: Single-View to Multi-View

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