Results 51 to 60 of about 1,461,923 (295)
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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IEEE Access, 2023 This study embarks on an in-depth analysis of the performance of various kernel functions, namely uniform, epanechnikov, triangular, and gaussian, in window-based and spectral clustering-based models.
Petr Silhavy, Radek Silhavy
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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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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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Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
Spectral clustering with epidemic diffusion [PDF]
Physical Review E, 2013 6 pages, to appear in Physical Review ...
Laura M. Smith +4 more
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FEBS Letters, EarlyView.Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
Spectral reordering of a range-dependent weighted random graph [PDF]
, 2005 Reordering under a random graph hypothesis can be regarded as an extension of clustering and fits into the general area of data mining. Here, we consider a generalization of Grindrod's model and show how an existing spectral reordering algorithm that has
Higham, D.J.
core +1 more source