Results 71 to 80 of about 9,565 (204)
Optimized clustering method for spectral reflectance recovery
Frontiers in Psychology, 2022 An optimized method based on dynamic partitional clustering was proposed for the recovery of spectral reflectance from camera response values. The proposed method produced dynamic clustering subspaces using a combination of dynamic and static clustering,
Yifan Xiong +3 more
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Robust Semi-Supervised Subspace Clustering via Non-Negative Low-Rank Representation
, 2016 Low-rank representation (LRR) has been successfully applied in exploring the subspace structures of data. However, in previous LRR-based semi-supervised subspace clustering methods, the label information is not used to guide the affinity matrix ...
Fang, Xiaozhao +9 more
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A Multi-View Co-Training Clustering Algorithm Based on Global and Local Structure Preserving
IEEE Access, 2021 Multi-view clustering which integrates the complementary information from different views for better clustering, is a fundamental and important topic in machine learning.
Weiling Cai, Honghan Zhou, Le Xu
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Dimensionality-reduced subspace clustering [PDF]
, 2021 Subspace clustering refers to the problem of clustering unlabeled high-dimensional data points into a union of low-dimensional linear subspaces, whose number, orientations and dimensions are all unknown. In practice, one may have access to dimensionality-
Bölcskei, Helmut +2 more
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Convolutional Subspace Clustering Network With Block Diagonal Prior
IEEE Access, 2020 Standard methods of subspace clustering are based on self-expressiveness in the original data space, which states that a data point in a subspace can be expressed as a linear combination of other points. However, the real data in raw form are usually not
Junjian Zhang +4 more
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Subspace clustering using ensembles of K-subspaces
Information and Inference: A Journal of the IMA, 2020 Abstract Subspace clustering is the unsupervised grouping of points lying near a union of low-dimensional linear subspaces. Algorithms based directly on geometric properties of such data tend to either provide poor empirical performance, lack theoretical guarantees or depend heavily on their initialization.
Lipor, John +3 more
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Fusion and Enhancement of Consensus Matrix for Multi-View Subspace Clustering
Mathematics, 2023 Multi-view subspace clustering is an effective method that has been successfully applied to many applications and has attracted the attention of scholars.
Xiuqin Deng, Yifei Zhang, Fangqing Gu
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Impact Parameter Analysis of Subspace Clustering
International Journal of Distributed Sensor Networks, 2015 Subspace clustering, which detects all clusters in affine subspaces of a given high dimensional vector space, is used in various applications, including e-business.
Dongjin Lee, Junho Shim
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Noisy Sparse Subspace Clustering
J. Mach. Learn. Res., 2013 Manuscript currently under review at journal of machine learning research.
Yu-Xiang Wang 0003, Huan Xu
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Iterative deep subspace clustering
, 2018 Recently, deep learning has been widely used for subspace clustering problem due to the excellent feature extraction ability of deep neural network. Most of the existing methods are built upon the auto-encoder networks.
Shuai Wang +10 more
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