Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
In this paper, we propose a new clustering model, called DEeP Embedded Regularized ClusTering (DEPICT), which efficiently maps data into a discriminative embedding subspace and precisely predicts cluster assignments. DEPICT generally consists of a multinomial logistic regression function stacked on top of a multi-layer convolutional autoencoder. We define a clustering …