Results 41 to 50 of about 64,517 (265)
A Note On Spectral Clustering.
CoRR, 2015 Spectral clustering is a popular and successful approach for partitioning the nodes of a graph into clusters for which the ratio of outside connections compared to the volume (sum of degrees) is small. In order to partition into k clusters, one first computes an approximation of the bottom k eigenvectors of the (normalized) Laplacian of G, uses it to ...
Kolev, Pavel, Mehlhorn, Kurt
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A Performance Guarantee for Spectral Clustering
SIAM Journal on Mathematics of Data Science, 2021 The two-step spectral clustering method, which consists of the Laplacian eigenmap and a rounding step, is a widely used method for graph partitioning. It can be seen as a natural relaxation to the NP-hard minimum ratio cut problem. In this paper we study the central question: when is spectral clustering able to find the global solution to the minimum ...
March Boedihardjo +2 more
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Average Sensitivity of Spectral Clustering [PDF]
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 KDD ...
Peng, P., Yoshida, Y.
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An Adaptive Spectral Clustering Algorithm Based on the Importance of Shared Nearest Neighbors
Algorithms, 2015 The construction of a similarity matrix is one significant step for the spectral clustering algorithm; while the Gaussian kernel function is one of the most common measures for constructing the similarity matrix.
Xiaoqi He, Sheng Zhang, Yangguang Liu
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Spectral clustering for jet physics
Journal of High Energy Physics, 2022 We present a new approach to jet definition alternative to clustering methods, such as the anti-kT scheme, that exploit kinematic data directly. Instead the new method uses kinematic information to represent the particles in a multidimensional space, as ...
Giorgio Cerro +5 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Embryonal tumors comprise the majority of malignant central nervous system (CNS) neoplasms diagnosed in children under 3 years of age. Compared with their counterparts in older children, these tumors exhibit distinct molecular biology and a more aggressive clinical phenotype, while their management is complicated by the heightened ...
Sudarshawn Damodharan +3 more
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Frontiers in Energy Research, 2022 Power system clustering is an effective method for realizing voltage control and preventing failure propagation. Various approaches are used for power system clustering. Graph-theory-based spectral clustering methods are widely used because they follow a
Juhwan Kim +5 more
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A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho +7 more
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Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
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Applications in Plant Sciences, 2020 Premise Statistical methods used by most morphologists to validate species boundaries (such as principal component analysis [PCA] and non‐metric multidimensional scaling [nMDS]) are limiting because these methods are mostly used as visualization methods,
Preeti Saryan +2 more
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