Applications of tensor (multiway array) factorizations and decompositions in data mining
M Mørup - Wiley Interdisciplinary Reviews: Data Mining and …, 2011 - Wiley Online Library
Tensor (multiway array) factorization and decomposition has become an important tool for
data mining. Fueled by the computational power of modern computer researchers can now …
data mining. Fueled by the computational power of modern computer researchers can now …
Tensor decompostions: state of the art and applications
P Comon - Institute of Mathematics and its Applications …, 2002 - books.google.com
In this paper, we present a partial survey of the tools borrowed from tensor algebra, which
have been utilized recently in Statistics and Signal Processing. It is shown why the …
have been utilized recently in Statistics and Signal Processing. It is shown why the …
Channel estimation for RIS-empowered multi-user MISO wireless communications
Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-
efficient solution for future wireless networks due to their fast and low-power configuration …
efficient solution for future wireless networks due to their fast and low-power configuration …
Tensor decomposition for signal processing and machine learning
Tensors or multiway arrays are functions of three or more indices (i, j, k,...)-similar to matrices
(two-way arrays), which are functions of two indices (r, c) for (row, column). Tensors have a …
(two-way arrays), which are functions of two indices (r, c) for (row, column). Tensors have a …
Coarray tensor direction-of-arrival estimation
Augmented coarrays can be derived from spatially undersampled signals of sparse arrays
for underdetermined direction-of-arrival (DOA) estimation. With the extended dimension of …
for underdetermined direction-of-arrival (DOA) estimation. With the extended dimension of …
Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions
Modern applications in engineering and data science are increasingly based on
multidimensional data of exceedingly high volume, variety, and structural richness …
multidimensional data of exceedingly high volume, variety, and structural richness …
Tensor decompositions for signal processing applications: From two-way to multiway component analysis
The widespread use of multisensor technology and the emergence of big data sets have
highlighted the limitations of standard flat-view matrix models and the necessity to move …
highlighted the limitations of standard flat-view matrix models and the necessity to move …
Big data analysis with signal processing on graphs: Representation and processing of massive data sets with irregular structure
A Sandryhaila, JMF Moura - IEEE signal processing magazine, 2014 - ieeexplore.ieee.org
Analysis and processing of very large data sets, or big data, poses a significant challenge.
Massive data sets are collected and studied in numerous domains, from engineering …
Massive data sets are collected and studied in numerous domains, from engineering …
Third-order tensors as operators on matrices: A theoretical and computational framework with applications in imaging
Recent work by Kilmer and Martin [Linear Algebra Appl., 435 (2011), pp. 641--658] and
Braman [Linear Algebra Appl., 433 (2010), pp. 1241--1253] provides a setting in which the …
Braman [Linear Algebra Appl., 433 (2010), pp. 1241--1253] provides a setting in which the …
Factorization strategies for third-order tensors
ME Kilmer, CD Martin - Linear Algebra and its Applications, 2011 - Elsevier
Operations with tensors, or multiway arrays, have become increasingly prevalent in recent
years. Traditionally, tensors are represented or decomposed as a sum of rank-1 outer …
years. Traditionally, tensors are represented or decomposed as a sum of rank-1 outer …