Discussion of "Exponential-family Embedding with Application to Cell Developmental Trajectories for Single-cell RNA-seq Data".

Journal Article (Journal Article)

Exponential-family singular value decomposition (eSVD) is a new approach for embedding multivariate data into a lower-dimensional space. It provides an elegant dimension reduction framework with flexibility to handle one-parameter exponential family distributions and proven consistency. This approach adds a valuable new tool to the toolbox of data analysts. Here we discuss a number of open problems and challenges that remain to be addressed in the future in order to unleash the full potential of eSVD and other similar approaches.

Full Text

Duke Authors

Cited Authors

  • Ji, Z; Ji, H

Published Date

  • 2021

Published In

Volume / Issue

  • 116 / 534

Start / End Page

  • 471 - 474

PubMed ID

  • 34744216

Pubmed Central ID

  • PMC8570643

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1080/01621459.2021.1880920


  • eng

Conference Location

  • United States