Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations
S Hansen, T Plantenga, TG Kolda - Optimization Methods and …, 2015 - Taylor & Francis
Tensor factorizations with nonnegativity constraints have found application in analysing data
from cyber traffic, social networks, and other areas. We consider application data best …
from cyber traffic, social networks, and other areas. We consider application data best …
Alternating nonnegative least squares-incorporated regularized symmetric latent factor analysis for undirected weighted networks
Abstract An Undirected Weighted Network (UWN) can be precisely quantified as an
adjacency matrix whose inherent characteristics are fully considered in a Symmetric …
adjacency matrix whose inherent characteristics are fully considered in a Symmetric …
Fast damped Gauss-Newton algorithm for sparse and nonnegative tensor factorization
AH Phan, P Tichavský… - 2011 IEEE International …, 2011 - ieeexplore.ieee.org
Alternating optimization algorithms for canonical polyadic decomposition (with/without
nonnegative constraints) often accompany update rules with low computational cost, but …
nonnegative constraints) often accompany update rules with low computational cost, but …
Novel hierarchical ALS algorithm for nonnegative tensor factorization
AH Phan, A Cichocki, K Matsuoka… - 2011 IEEE International …, 2011 - ieeexplore.ieee.org
The multiplicative algorithms are well-known for nonnegative matrix and tensor
factorizations. The ALS algorithm for canonical decomposition (CP) has been proved as a" …
factorizations. The ALS algorithm for canonical decomposition (CP) has been proved as a" …
2D-seismic random-noise attenuation by self-pace nonnegative dictionary learning
Seismic random noise always exists in seismic data acquisition. Dictionary learning
methods are the effective tools to find a typical sparse representation. It can be introduced to …
methods are the effective tools to find a typical sparse representation. It can be introduced to …
[引用][C] Nonnegative DEDICOM based on tensor decompositions for social networks exploration
AH Phan, A Cichocki, T Vu-Dinh - Australian Journal of Intelligent Information …, 2010