Results 11 to 20 of about 3,374,256 (360)
Quantum spectral clustering [PDF]
Physical Review A, 2020 Spectral clustering is a powerful unsupervised machine learning algorithm for clustering data with non convex or nested structures. With roots in graph theory, it uses the spectral properties of the Laplacian matrix to project the data in a low ...
Iordanis Kerenidis, Jonas Landman
semanticscholar +5 more sources
Spectral Embedded Deep Clustering [PDF]
Entropy, 2019 We propose a new clustering method based on a deep neural network. Given an unlabeled dataset and the number of clusters, our method directly groups the dataset into the given number of clusters in the original space.
Yuichiro Wada +5 more
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Spectral Clustering with Imbalanced Data [PDF]
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013 Spectral clustering is sensitive to how graphs are constructed from data particularly when proximal and imbalanced clusters are present. We show that Ratio-Cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced data since they tend
Qian, Jing, Saligrama, Venkatesh
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Power Spectral Clustering [PDF]
Journal of Mathematical Imaging and Vision, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Challa, Aditya +3 more
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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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Hierarchical kernel spectral clustering [PDF]
Neural Networks, 2012 Kernel spectral clustering fits in a constrained optimization framework where the primal problem is expressed in terms of high-dimensional feature maps and the dual problem is expressed in terms of kernel evaluations. An eigenvalue problem is solved at the training stage and projections onto the eigenvectors constitute the clustering model.
Alzate Perez, Carlos, Suykens, Johan
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A Spectral Clustering Algorithm Based on Fuzzy Kernel Clustering [PDF]
Jisuanji gongcheng, 2017 Spectral clustering eigenvector of the Laplace matrix is not limited to the distribution shape of the original data and can converge to the global optimal solution,but it cannot accurately reflect the actual relationship between samples.However,fuzzy ...
FAN Zijing,LUO Ze,MA Yongzheng
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Fast Graph Clustering Algorithm Based on Selection of Key Nodes
Jisuanji kexue yu tansuo, 2021 Spectral clustering has attracted extensive attention as a typical graph clustering algorithm among clustering algorithms since it has really strong adaptability to complex data distribution and great clustering effect.
YOU Fangzhou, BAI Liang
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Spectral clustering based on the local similarity measure of shared neighbors
ETRI Journal, 2022 Spectral clustering has become a typical and efficient clustering method used in a variety of applications. The critical step of spectral clustering is the similarity measurement, which largely determines the performance of the spectral clustering method.
Zongqi Cao, Hongjia Chen, Xiang Wang
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Brain tumour segmentation from MRI using superpixels based spectral clustering
Journal of King Saud University: Computer and Information Sciences, 2020 The automated brain tumour segmentation method is becoming challenging in the field of medical research as a brain tumour emerges with diverse size, shape and intensity.
Angulakshmi Maruthamuthu +1 more
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