Results 61 to 70 of about 74,563 (305)
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
openaire +3 more sources
MACOC: a medoid-based ACO clustering algorithm [PDF]
, 2014 The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning
Otero, Fernando E. B. +7 more
core +1 more source
Transfer Spectral Clustering [PDF]
, 2012 Transferring knowledge from auxiliary datasets has been proved useful in machine learning tasks. Its adoption in clustering however is still limited. Despite of its superior performance, spectral clustering has not yet been incorporated with knowledge transfer or transfer learning.
Wenhao Jiang, Fu-Lai Chung
openaire +1 more source
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
doaj +1 more source
Multi-agent Behaviour Segmentation via Spectral Clustering [PDF]
, 2007 18.02.14 KB. OK to add accepted version to spiral, AAAI permits.We examine the application of spectral clustering for breaking up the behaviour of a multi-agent system in space and time into smaller, independent elements.
Takács, B, Demiris, Y, Butler, S
core
, 2015 Intentional controlled islanding is an effective corrective approach to minimise the impact of cascading outages leading to large-area blackouts. This study proposes a novel methodology, based on `constrained spectral clustering', that is computationally
Quiros-Tortos, Jairo +4 more
core +1 more source
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
wiley +1 more source
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
doaj +1 more source
Techniques for clustering gene expression data [PDF]
, 2008 Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments. However, choice of suitable method(s) for a given experimental dataset is not straightforward. Common approaches do not translate
Kerr, Gráinne +7 more
core +1 more source
Reciprocal control of viral infection and phosphoinositide dynamics
FEBS Letters, EarlyView.Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source