Clustering large graphs via the singular value decomposition
From MaRDI portal
Publication:703073
DOI10.1023/B:MACH.0000033113.59016.96zbMath1089.68090OpenAlexW2004791924WikidataQ55921971 ScholiaQ55921971MaRDI QIDQ703073
V. Vinay, Santosh Vempala, Ravindran Kannan, Alan M. Frieze, Petros Drineas
Publication date: 19 January 2005
Published in: Machine Learning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1023/b:mach.0000033113.59016.96
Related Items
Point clustering via voting maximization, Exact algorithms of searching for the largest size cluster in two integer 2-clustering problems, An improved primal-dual approximation algorithm for the k-means problem with penalties, A selection process for genetic algorithm using clustering analysis, A survey on feature weighting based K-means algorithms, Far-field compression for fast kernel summation methods in high dimensions, An exact algorithm for stable instances of the \(k\)-means problem with penalties in fixed-dimensional Euclidean space, Regularity of densities in relaxed and penalized average distance problem, Structural conditions for projection-cost preservation via randomized matrix multiplication, SVD, discrepancy, and regular structure of contingency tables, The provably good parallel seeding algorithms for the k‐means problem with penalties, On the complexity of some problems of searching for a family of disjoint clusters, Sparsified randomization algorithms for low rank approximations and applications to integral equations and inhomogeneous random field simulation, How to find a good explanation for clustering?, Global optimality in \(k\)-means clustering, k-means-g*: accelerating \(k\)-means clustering algorithm utilizing primitive geometric concepts, A Sparse Stress Model, HC\_AB: a new heuristic clustering algorithm based on approximate backbone, On constrained spectral clustering and its applications, Anomaly detection in large-scale data stream networks, The planar \(k\)-means problem is NP-hard, The singular values and vectors of low rank perturbations of large rectangular random matrices, Exemplar-based low-rank matrix decomposition for data clustering, The complexity of finding uniform sparsest cuts in various graph classes, Unnamed Item, Graph clustering, Embedding-based silhouette community detection, Embedding Graphs into Larger Graphs: Results, Methods, and Problems, Multiple Nested Reductions of Single Data Modes as a Tool to Deal with Large Data Sets, Local Search Yields a PTAS for $k$-Means in Doubling Metrics, The Complexity Status of Problems Related to Sparsest Cuts, The Parallel Seeding Algorithm for k-Means Problem with Penalties, Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering, Approximation algorithms for fuzzy \(C\)-means problem based on seeding method, PCA and SVD with nonnegative loadings, Matrix recipes for hard thresholding methods, On the isoperimetric spectrum of graphs and its approximations, An approximation ratio for biclustering, Rederivation of the fuzzy-possibilistic clustering objective function through Bayesian inference, Recognizing linear structure in noisy matrices, On the information and representation of non-Euclidean pairwise data, Singular value decomposition in additive, multiplicative, and logistic forms, The Planar k-Means Problem is NP-Hard, Robust K-Median and K-means clustering algorithms for incomplete data, Asymptotic regularity of subdivisions of Euclidean domains by iterated PCA and iterated 2-means, A New Troubled-Cell Indicator for Discontinuous Galerkin Methods Using K-Means Clustering, The seeding algorithm for \(k\)-means problem with penalties, Stochastic Algorithms in Linear Algebra - beyond the Markov Chains and von Neumann - Ulam Scheme, NP-hardness of Euclidean sum-of-squares clustering, ORCA: outlier detection and robust clustering for attributed graphs, \(k\)-Mnv-Rep: a \(k\)-type clustering algorithm for matrix-object data, The seeding algorithms for spherical \(k\)-means clustering, The bi-criteria seeding algorithms for two variants of \(k\)-means problem, An approximation algorithm for the uniform capacitated \(k\)-means problem, The seeding algorithm for spherical \(k\)-means clustering with penalties, Unnamed Item, Unnamed Item, Fast and Accurate Proper Orthogonal Decomposition using Efficient Sampling and Iterative Techniques for Singular Value Decomposition