Alwin Stegeman

According to our database1, Alwin Stegeman authored at least 16 papers between 2006 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2019
Rayleigh Quotient Methods for Estimating Common Roots of Noisy Univariate Polynomials.
Comput. Methods Appl. Math., 2019

2017
On the Largest Multilinear Singular Values of Higher-Order Tensors.
SIAM J. Matrix Anal. Appl., 2017

2016
A new method for simultaneous estimation of the factor model parameters, factor scores, and unique parts.
Comput. Stat. Data Anal., 2016

2014
Finding the limit of diverging components in three-way Candecomp/Parafac - A demonstration of its practical merits.
Comput. Stat. Data Anal., 2014

2013
A Three-Way Jordan Canonical Form as Limit of Low-Rank Tensor Approximations.
SIAM J. Matrix Anal. Appl., 2013

2012
CONFAC Decomposition Approach to Blind Identification of Underdetermined Mixtures Based on Generating Function Derivatives.
IEEE Trans. Signal Process., 2012

Improved Uniqueness Conditions for Canonical Tensor Decompositions with Linearly Dependent Loadings.
SIAM J. Matrix Anal. Appl., 2012

Candecomp/Parafac: From Diverging Components to a Decomposition in Block Terms.
SIAM J. Matrix Anal. Appl., 2012

Uni-mode and Partial Uniqueness Conditions for CANDECOMP/PARAFAC of Three-Way Arrays with Linearly Dependent Loadings.
SIAM J. Matrix Anal. Appl., 2012

2011
On Uniqueness of the Canonical Tensor Decomposition with Some Form of Symmetry.
SIAM J. Matrix Anal. Appl., 2011

2010
On Uniqueness of the nth Order Tensor Decomposition into Rank-1 Terms with Linear Independence in One Mode.
SIAM J. Matrix Anal. Appl., 2010

2009
Uniqueness Conditions for Constrained Three-Way Factor Decompositions with Linearly Dependent Loadings.
SIAM J. Matrix Anal. Appl., 2009

Subtracting a best rank-1 approximation may increase tensor rank.
Proceedings of the 17th European Signal Processing Conference, 2009

2008
A Method to Avoid Diverging Components in the Candecomp/Parafac Model for Generic I˟J˟2 Arrays.
SIAM J. Matrix Anal. Appl., 2008

Low-Rank Approximation of Generic p˟q˟2 Arrays and Diverging Components in the Candecomp/Parafac Model.
SIAM J. Matrix Anal. Appl., 2008

2006
Kruskal's condition for uniqueness in Candecomp/Parafac when ranks and k.
Comput. Stat. Data Anal., 2006


  Loading...