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Joint unsupervised learning of deep representations and image clusters
Joint unsupervised learning of deep representations and image clusters -
Unsupervised deep embedding for clustering analysis
Unsupervised deep embedding for clustering analysis -
Deep Embedding Clustering Driven by Sample Stability
Deep embedding clustering algorithm driven by sample stability -
UCI datasets
The dataset used in the paper is a set of UCI datasets, including adult, census, covertype, financial, joke, mushroom, and statlog. -
MNIST-full, MNIST-test, USPS, Fashion-Mnist, YTF
The dataset used in the paper is a benchmark dataset for clustering, including MNIST-full, MNIST-test, USPS, Fashion-Mnist, and YTF. -
USPS dataset
The USPS dataset consists of 9298 images of handwritten digits 0-9 (10 classes) of 16x16 pixels in gray scale. -
SELF-LABELLING VIA SIMULTANEOUS CLUSTERING AND REPRESENTATION LEARNING
Combining clustering and representation learning is one of the most promising approaches for unsupervised learning of deep neural networks. -
Real-world dataset
The dataset used in this paper for testing the 3D-RecGAN++ model. It contains 1.5k SV and 2.5k CV testing datasets for each of the 6 categories. -
Unsupervised Clustered Federated Learning in Complex Multi-source Acoustic En...
The dataset is a complex multi-source acoustic environment and an improved algorithm for the estimation of source-dominated microphone clusters in acoustic sensor networks. -
Iris dataset
The Iris dataset is a multivariate dataset introduced by Sir Ronald Fisher in his 1936 paper "The use of multiple measurements in taxonomic problems". It contains 150 samples... -
Orthogonalization of data via Gromov-Wasserstein type feedback for clustering...
The dataset is used for clustering and visualization of data by an orthogonalization process. -
Bank Marketing
The dataset comprises of phone call records of a marketing campaign run by a Portuguese bank. The marital status of the clients is considered feature to ensure fairness.
