Results 51 to 60 of about 56,202 (281)
High Dimensional Classification with combined Adaptive Sparse PLS and Logistic Regression [PDF]
, 2017 Motivation: The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent over-optimistic predictions. This challenge can be tackled by compression and variable selection, which combined
Durif, G. +5 more
core +4 more sources
Feature selection guided by structural information [PDF]
, 2009 In generalized linear regression problems with an abundant number of features, lasso-type regularization which imposes an $\ell^1$-constraint on the regression coefficients has become a widely established technique.
Castell, Wolfgang zu +2 more
core +2 more sources
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
, 2018 In this paper, we consider the nonparametric regression problem with multivariate predictors. We provide a characterization of the degrees of freedom and divergence for estimators of the unknown regression function, which are obtained as outputs of ...
Chen, Xi, Lin, Qihang, Sen, Bodhisattva
core +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Condition numbers of the generalized ridge regression and its statistical estimation
AIMS MathematicsIn this paper, we considered the condition number theory of a new generalized ridge regression model. The explicit expressions of different types of condition numbers were derived to measure the ill-conditionness of the generalized ridge regression ...
Jing Kong , Shaoxin Wang
doaj +1 more source
Advanced Healthcare Materials, EarlyView.Hybrid wrinkled topographies coordinate immune, tissue, and bacterial interactions. The surfaces promote osteointegration, tune macrophage polarization, and inhibit biofilm formation, highlighting a multifunctional strategy for next‐generation implant design.
Mohammad Asadi Tokmedash +4 more
wiley +1 more source
Asymptotics of Ridge (less) Regression under General Source Condition
, 2020 We analyze the prediction error of ridge regression in an asymptotic regime where the sample size and dimension go to infinity at a proportional rate. In particular, we consider the role played by the structure of the true regression parameter. We observe that the case of a general deterministic parameter can be reduced to the case of a random ...
Dominic Richards +2 more
openaire +3 more sources
Advanced Healthcare Materials, EarlyView.A compact handheld GelSight probe reconstructs in vivo 3‐D skin topography with micron‐level precision using a custom elastic gel and a learning‐based surface normal to height map pipeline. The device quantifies wrinkle depth across various body locations and detects changes in wrinkle depth following moisturizer application.
Akhil Padmanabha +12 more
wiley +1 more source
Frontiers in Genetics, 2020 Genome-Wide Association Studies (GWAS) explain only a small fraction of heritability for most complex human phenotypes. Genomic heritability estimates the variance explained by the SNPs on the whole genome using mixed models and accounts for the many ...
Arthur Frouin +6 more
doaj +1 more source