SGL-SVM: a novel method for tumor classification via support vector machine with sparse group Lasso.
Sign Up to like & getrecommendations! Published in 2019 at "Journal of theoretical biology"
DOI: 10.1016/j.jtbi.2019.110098
Abstract: At present, with the in-depth study of gene expression data, the significant role of tumor classification in clinical medicine has become more apparent. In particular, the sparse characteristics of gene expression data within and between… read more here.
Keywords: classification; sgl svm; group lasso; tumor classification ... See more keywords
Overcoming the inadaptability of sparse group lasso for data with various group structures by stacking
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab848
Abstract: MOTIVATION Efficiently identifying genes based on gene expression level have been studied to help to classify different cancer types and improve the prediction performance. Logistic regression model based on regularization technique is often one of… read more here.
Keywords: group; inadaptability sparse; feature; selection ... See more keywords
A Fitted Sparse-Group Lasso for Genome-Based Evaluations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2022.3156805
Abstract: In life sciences, high-throughput techniques typically lead to high-dimensional data and often the number of covariates is much larger than the number of observations. This inherently comes with multicollinearity challenging a statistical analysis in a… read more here.
Keywords: group lasso; lasso genome; genome based; group ... See more keywords
Feature Selection for Neural Networks Using Group Lasso Regularization
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2019.2893266
Abstract: We propose an embedded/integrated feature selection method based on neural networks with Group Lasso penalty. Group Lasso regularization is considered to produce sparsity on the inputs to the network, i.e., for selection of useful features.… read more here.
Keywords: feature selection; neural networks; group; group lasso ... See more keywords
A Novel Pruning Algorithm for Smoothing Feedforward Neural Networks Based on Group Lasso Method
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2017.2748585
Abstract: In this paper, we propose four new variants of the backpropagation algorithm to improve the generalization ability for feedforward neural networks. The basic idea of these methods stems from the Group Lasso concept which deals… read more here.
Keywords: neural networks; novel pruning; group; pruning algorithm ... See more keywords
Sparse-Group Lasso for Graph Learning From Multi-Attribute Data
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2021.3057699
Abstract: We consider the problem of inferring the conditional independence graph (CIG) of high-dimensional Gaussian vectors from multi-attribute data. Most existing methods for graph estimation are based on single-attribute models where one associates a scalar random… read more here.
Keywords: multi attribute; sparse group; attribute data; graph ... See more keywords
Oracle inequalities for weighted group lasso in high-dimensional misspecified Cox models
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Inequalities and Applications"
DOI: 10.1186/s13660-020-02517-3
Abstract: We study the nonasymptotic properties of a general norm penalized estimator, which include Lasso, weighted Lasso, and group Lasso as special cases, for sparse high-dimensional misspecified Cox models with time-dependent covariates. Under suitable conditions on… read more here.
Keywords: high dimensional; group; misspecified cox; group lasso ... See more keywords
Genetic Variants Detection Based on Weighted Sparse Group Lasso
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2020.00155
Abstract: Identification of genetic variants associated with complex traits is a critical step for improving plant resistance and breeding. Although the majority of existing methods for variants detection have good predictive performance in the average case,… read more here.
Keywords: variants detection; genetic variants; group; group lasso ... See more keywords
A Disentangled Representation Based Brain Image Fusion via Group Lasso Penalty
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2022.937861
Abstract: Complementary and redundant relationships inherently exist between multi-modal medical images captured from the same brain. Fusion processes conducted on intermingled representations can cause information distortion and the loss of discriminative modality information. To fully exploit… read more here.
Keywords: fusion; brain; image fusion; lasso penalty ... See more keywords