Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection

no code implementations • 29 Oct 2020 • Imtiaz Ahmed, Travis Galoppo, Xia Hu, Yu Ding

In order to make dimensionality reduction effective for high-dimensional data embedding nonlinear low-dimensional manifold, it is understood that some sort of geodesic distance metric should be used to discriminate the data samples.

Clustering Dimensionality Reduction +1