Shifted factor analysis—Part I: Models and properties

By Richard A. Harshman, Sungjin Hong, M. E. Lundy. 2003

70 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Applied Mathematics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/adb99a119c98d80154fed0d3390c17a72bf5f424

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Christos Faloutsos
2. Tamara G. Kolda
3. Evangelos E. Papalexakis
4. Evrim Acar
5. Brett W. Bader
6. N. Sidiropoulos
7. Bülent Yener

In Applied Mathematics

1. Evrim Acar
2. Bülent Yener

In Signal Processing

1. Tamara G. Kolda
2. Evrim Acar
3. Christos Faloutsos
4. Evangelos E. Papalexakis
5. N. Sidiropoulos
6. Brett W. Bader
7. Boris N. Khoromskij
8. Daniel M. Dunlavy

Citations in the corpus

• Tensors for Data Mining and Data Fusion (2016, background): “To solve that, Mørup et al. [2008], following up on Harshman et al. [2003], propose a modification to the CP model, the shift invariant CP (Shift-CP), which takes the time shift into account.”
• Unsupervised Multiway Data Analysis: A Literature Survey (2009, methodology): “. cPARAFAC [31]: Another extension of a PARAFAC model is cPARAFAC, which is a generalization of Nonnegative Matrix Factor Deconvolution (NMFD) to multiway spectral data. cPARAFAC, closely related to S-PARAFAC, has been proposed for multichannel spectral data analysis in order to model convolutive mi”
• Tensor Decompositions and Applications (2009, background): “Acar and Yener [6] discuss several of these decompositions as well as some not covered here: shifted CP and Tucker [97] and convoluted CP [171].”