Search results with tag "Unsupervised deep embedding for clustering analysis"

Unsupervised Deep Embedding for Clustering Analysis

Several variants of k-means have been proposed to address issues with higher-dimensional input spaces.De la Torre & Kanade(2006);Ye et al.(2008) perform joint dimension-ality reduction and clustering by first clustering the data with k-means and then projecting the data into a lower di-mensions where the inter-cluster variance is maximized.

  Analysis, Name, Deep, Embedding, Unsupervised, Clustering, Unsupervised deep embedding for clustering analysis