• Kernlab

  • Referenced in 104 articles [sw07926]
  • based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction ... methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes...
  • LAMG

  • Referenced in 34 articles [sw06551]
  • applications such as semisupervised machine learning; spectral clustering of images, genetic data, and web pages...
  • clusterpath

  • Referenced in 29 articles [sw41747]
  • proposing a convex relaxation of hierarchical clustering, which results in a family of objective functions ... results similar to spectral clustering for non-convex clusters, and has the added benefit...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • Recent developments are in kernel spectral clustering, data visualization and dimensionality reduction, and survival analysis...
  • SymNMF

  • Referenced in 15 articles [sw12668]
  • study an extended formulation for graph clustering called Symmetric NMF (SymNMF). In contrast ... show that SymNMF is related to spectral clustering, justify SymNMF as a general graph clustering ... strengths and shortcomings of SymNMF and spectral clustering. We propose two optimization algorithms for SymNMF...
  • SpectralCAT

  • Referenced in 8 articles [sw18794]
  • SpectralCAT: Categorical spectral clustering of numerical and nominal data. Data clustering is a common technique ... automated technique, called SpectralCAT, for unsupervised clustering of high-dimensional data that contains numerical ... dataset. Then, a method for spectral clustering via dimensionality reduction of the transformed data...
  • IsoRankN

  • Referenced in 11 articles [sw08325]
  • multiple-network alignment tool based on spectral clustering on the induced graph of pairwise alignment ... five available eukaryotic networks. Being based on spectral methods, IsoRankN is both error-tolerant...
  • SpectralNet

  • Referenced in 6 articles [sw26162]
  • SpectralNet: Spectral Clustering using Deep Neural Networks. Spectral clustering is a leading and popular technique ... limitations are scalability and generalization of the spectral embedding (i.e., out-of-sample-extension ... introduce a deep learning approach to spectral clustering that overcomes the above shortcomings. Our network ... spectral embedding to unseen data points. To further improve the quality of the clustering...
  • PEGASUS

  • Referenced in 8 articles [sw17479]
  • MapReduce. Many graph mining operations (PageRank, spectral clustering, diameter estimation, connected components etc.) are essentially...
  • ClusterES

  • Referenced in 10 articles [sw18311]
  • spectral scheme for Kohn-Sham density functional theory of clusters. Starting from the observation that ... systems - the plane-wave method - is a spectral method based on eigenfunction expansion ... formulate a spectral method designed towards solving the Kohn-Sham equations for clusters. This allows...
  • clusterSim

  • Referenced in 6 articles [sw16124]
  • Bray-Curtis, for symbolic interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, Hubert ... method, replication analysis, linear ordering methods, spectral clustering, agreement indices between two partitions, plot functions...
  • BoostCluster

  • Referenced in 5 articles [sw08555]
  • clustering algorithms (K-means, partitional SingleLink, spectral clustering), and its performance is comparable...
  • DIFFRAC

  • Referenced in 5 articles [sw23902]
  • readily extended to non linear clustering if the discriminative cost function is based on positive ... seen as an alternative to spectral clustering. (3) Prior information on the partition is easily...
  • HSMClust

  • Referenced in 6 articles [sw25560]
  • hierarchical spectral merger algorithm: a new time series clustering procedure. We present ... method for time series clustering which we call the Hierarchical Spectral Merger (HSM) method. This ... algorithm, every time two clusters merge, a new spectral density is estimated using the whole...
  • GraphLSH

  • Referenced in 2 articles [sw40698]
  • GraphLSHC: towards large scale spectral hypergraph clustering. Hypergraph is popularly used for describing multi-relationships ... objects in a unified manner, and spectral clustering is regarded as one of the most ... into different communities. However, the traditional spectral clustering for hypergraph (HC) incurs expensive costs ... faced by the large scale hypergraph spectral clustering. In our solution, the hypergraph used...
  • Power-Spectral-Clustering

  • Referenced in 1 article [sw36494]
  • Power spectral clustering. Spectral clustering is one of the most important image processing tools, especially ... widely applicable. However, traditional spectral clustering is ({mathcal{O}}(n^{3/2})). This poses a challenge ... maximum spanning tree clustering and spectral clustering. This algorithm scales as ({mathcal ... which are similar to that of spectral clustering. Several toy examples are used to illustrate...
  • jClust

  • Referenced in 1 article [sw21913]
  • search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut...
  • Kernel Cut

  • Referenced in 1 article [sw38990]
  • Kernel cuts: kernel and spectral clustering meet regularization. This work bridges the gap between ... popular methodologies for data partitioning: kernel clustering and regularization-based segmentation. While addressing closely related ... spectral relaxation versus max-flow. We explain how regularization and kernel clustering can work together ... linear kernel and spectral bounds for kernel clustering criteria allowing their integration with any regularization...
  • Multiview

  • Referenced in 1 article [sw39394]
  • advantage of using multiview methods of clustering and dimensionality reduction; however, none of these methods ... embedding, as well as a multiview spectral clustering method. Often they produce better results than...
  • GraphDemo

  • Referenced in 1 article [sw10148]
  • dimensionality reduction or data denoising, spectral clustering, label propagation for semi-supervised learning...