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Computing the Sparsity Pattern of Hessians Using Automatic Differentiation
(Assoc Computing MachineryNew YorkEUA, 2014)
Wavelet shrinkage using adaptive structured sparsity constraints
(Elsevier, 2015-01)
Structured sparsity approaches have recently received much attention in the statistics, machine learning, and signal processing communities. A common strategy is to exploit or assume prior information about structural ...
A study of LMS-based algorithms: exploiting plain and hidden sparsityUm estudo de algoritmos baseados em LMS: explorando esparsidade simples e escondida
(Universidade Federal do Rio de JaneiroBrasilInstituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de EngenhariaPrograma de Pós-Graduação em Engenharia ElétricaUFRJ, 2021)
Finding archetypal patterns for binary questionnaires
One of the main challenges researchers face is to identify the most relevant features in a prediction model. As a consequence, many regularized methods seeking sparsity have flourished. Although sparse, their solutions may ...
On the existence of the weighted bridge penalized Gaussian likelihood precision matrix estimator
(The Institute of Mathematical Statistics and the Bernoulli Society, 2014-12)
We establish a necessary and sufficient condition for the existence of the precision matrix estimator obtained by minimizing the negative Gaussian log-likelihood plus a weighted bridge penalty. This condition enables us ...
A W-matrix methodology for solving sparse network equations on multiprocessor computers
(Institute of Electrical and Electronics Engineers (IEEE), 1992-08-01)
This paper describes a methodology for solving efficiently the sparse network equations on multiprocessor computers. The methodology is based on the matrix inverse factors (W-matrix) approach to the direct solution phase ...
A W-matrix methodology for solving sparse network equations on multiprocessor computers
(Institute of Electrical and Electronics Engineers (IEEE), 1992-08-01)
This paper describes a methodology for solving efficiently the sparse network equations on multiprocessor computers. The methodology is based on the matrix inverse factors (W-matrix) approach to the direct solution phase ...
A W-matrix methodology for solving sparse network equations on multiprocessor computers
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
Sparsity-driven synchronization in oscillator networks
(2022-03-01)
The emergence of synchronized behavior is a direct consequence of networking dynamical systems. Naturally, strict instances of this phenomenon, such as the states of complete synchronization, are favored or even ensured ...