A Preconditioned Conjugate Gradient Method with Active Set Strategy for $$\ell _1$$ℓ1-Regularized Least Squares
Sign Up to like & getrecommendations! Published in 2018 at "Journal of the Operations Research Society of China"
DOI: 10.1007/s40305-018-0202-x
Abstract: In the paper, we consider the $$\ell _1$$ℓ1-regularized least square problem which has been intensively involved in the fields of signal processing, compressive sensing, linear inverse problems and statistical inference. The considered problem has been… read more here.
Keywords: gradient method; ell regularized; conjugate gradient; regularized least ... See more keywords
Regularized least absolute deviation-based sparse identification of dynamical systems.
Sign Up to like & getrecommendations! Published in 2023 at "Chaos"
DOI: 10.1063/5.0130526
Abstract: This work develops a regularized least absolute deviation-based sparse identification of dynamics (RLAD-SID) method to address outlier problems in the classical metric-based loss function and the sparsity constraint framework. Our method uses absolute derivation loss… read more here.
Keywords: least absolute; identification; absolute deviation; based sparse ... See more keywords
SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association
Sign Up to like & getrecommendations! Published in 2019 at "RNA Biology"
DOI: 10.1080/15476286.2019.1694732
Abstract: ABSTRACT Accumulating studies have shown that microRNAs (miRNAs) could be used as targets of small-molecule (SM) drugs to treat diseases. In recent years, researchers have proposed many computational models to reveal miRNA-SM associations due to… read more here.
Keywords: molecule; small molecule; nonnegative matrix; matrix factorization ... See more keywords
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac292
Abstract: Increasing biomedical evidence has proved that the dysregulation of miRNAs is associated with human complex diseases. Identification of disease-related miRNAs is of great importance for disease prevention, diagnosis and remedy. To reduce the time and… read more here.
Keywords: disease; dual laplacian; disease associations; mirna disease ... See more keywords
Learning rates for regularized least squares ranking algorithm
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DOI: 10.1142/s0219530517500063
Abstract: The ranking problem aims at learning real-valued functions to order instances, which has attracted great interest in statistical learning theory. In this paper, we consider the regularized least squares ranking algorithm within the framework of… read more here.
Keywords: least squares; learning rates; ranking algorithm; rates regularized ... See more keywords
Finding Lung-Cancer-Related lncRNAs Based on Laplacian Regularized Least Squares With Unbalanced Bi-Random Walk
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.933009
Abstract: Lung cancer is one of the leading causes of cancer-related deaths. Thus, it is important to find its biomarkers. Furthermore, there is an increasing number of studies reporting that long noncoding RNAs (lncRNAs) demonstrate dense… read more here.
Keywords: lung cancer; random walk; cancer; regularized least ... See more keywords
mintRULS: Prediction of miRNA–mRNA Target Site Interactions Using Regularized Least Square Method
Sign Up to like & getrecommendations! Published in 2022 at "Genes"
DOI: 10.3390/genes13091528
Abstract: Identification of miRNA–mRNA interactions is critical to understand the new paradigms in gene regulation. Existing methods show suboptimal performance owing to inappropriate feature selection and limited integration of intuitive biological features of both miRNAs and… read more here.
Keywords: mirna mrna; target; target site; method ... See more keywords