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Bregman Power k-Means
Exponential family data -
Entropy Payload
The dataset used in the paper is a series of data points with 21 numbers, and the similarity between data is measured by the difference between numbers. -
Radiology reports dataset
Radiology reports dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm. -
NIPS dataset
NIPS dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm. -
Hierarchical Latent Word Clustering
Hierarchical Latent Word Clustering dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm. -
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative En...
Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization. -
Deep Variational Clustering Framework for Self-labeling of Large-scale Medica...
The proposed framework is composed of two networks (see Fig 1). The encoder network q with parameters of φ computes qφ(z|x) : xi → zi. The encoder maps an input image xi ∈ X to... -
Clustering and Semi-Supervised Classification for Clickstream Data via Mixture...
Clickstream data is one of the various emerging data types that demands particular attention because there is a notable paucity of statistical learning approaches currently... -
Generating Object Cluster Hierarchies for Benchmarking
Object Cluster Hierarchy (OCH) is a novel variant of Hierarchical Clustering that increasingly gains more interest in the field of Machine Learning. -
Image Segmentation
The Image Segmentation dataset is used to evaluate the performance of the ensemble average rule. -
Newsgroups 4
The dataset used in this paper for Dominant Set Clustering. -
Newsgroups 3
The dataset used in this paper for Dominant Set Clustering. -
Newsgroups 2
The dataset used in this paper for Dominant Set Clustering. -
Dominant Set Clustering
The dataset used in this paper for Dominant Set Clustering. -
Breast Cancer Dataset
Breast cancer dataset where mammograms have been labeled independently by three doctors. Ground-truth has been obtained through a biopsy, not available to the algorithm nor the... -
DBSCAN Dataset
The dataset is used to evaluate the performance of clustering algorithms. -
k-meansNet: When k-means Meets Differentiable Programming
The proposed k-meansNet is used for clustering and has explicit interpretability in structure. -
Dirichlet-Survival Process: Scalable Inference of Topic-Dependent Diffusion Ne...
The Houston model jointly considers all three features: documents' content, time of publication relative to other publications, and position of the spreader in the network. -
Noisy Scale
The dataset used in the paper is a synthetic 2D dataset generated from a Gaussian Mixture Model. -
GMM Clustering
The dataset used in the paper is a synthetic 2D dataset generated from a Gaussian Mixture Model.
