Work

Adapting to data sparsity for efficient parallel PARAFAC tensor decomposition in Hadoop

Year: 2016

Type: conference-paper

Source: IEEE International Conference on Big Data (BigData)

DOI: 10.1109/bigdata.2016.7840615

Authors: Kareem S. Aggour, Bulent Yener

Institutions: GE Global Research (United States), Rensselaer Polytechnic Institute

Language: English

Topic: Tensor decomposition and applications

Subfield: Computational Mathematics

Field: Mathematics

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W2583925808

FWCI: 0.441

Cites: 18

Cited by: 2

Related to: 10