Results 51 to 60 of about 379,537 (253)

Generalized co-sparse factor regression

Computational Statistics & Data Analysis, 2021
Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors. In real-world applications, the outcomes are often of mixed types, including continuous measurements, binary indicators, and counts, and the observations may also be incomplete. Building upon the recent advances in mixed-
Mishra, Aditya, Dey, Dipak K., Chen, Yong, Chen, Kun   +3 more
openaire   +3 more sources

Sparse Regression with Multi-type Regularized Feature Modeling

, 2020
Within the statistical and machine learning literature, regularization techniques are often used to construct sparse (predictive) models. Most regularization strategies only work for data where all predictors are treated identically, such as Lasso ...
Antonio, Katrien, Devriendt, Sander, Reynkens, Tom, Verbelen, Roel   +3 more
core   +1 more source

Adaptive L0 Regularization for Sparse Support Vector Regression

Mathematics, 2023
In this work, we proposed a sparse version of the Support Vector Regression (SVR) algorithm that uses regularization to achieve sparsity in function estimation.
Antonis Christou, Andreas Artemiou
doaj   +1 more source

Sparse Tensor Additive Regression

, 2019
Tensors are becoming prevalent in modern applications such as medical imaging and digital marketing. In this paper, we propose a sparse tensor additive regression (STAR) that models a scalar response as a flexible nonparametric function of tensor covariates.
Hao, Botao, Wang, Boxiang, Wang, Pengyuan, Zhang, Jingfei, Yang, Jian, Sun, Will Wei   +5 more
openaire   +3 more sources

Joint Sparse Sub-Pixel Mapping Model with Endmember Variability for Remotely Sensed Imagery

Remote Sensing, 2016
Spectral unmixing and sub-pixel mapping have been used to estimate the proportion and spatial distribution of the different land-cover classes in mixed pixels at a sub-pixel scale. In the past decades, several algorithms were proposed in both categories;
Xiong Xu, Xiaohua Tong, Antonio Plaza, Yanfei Zhong, Huan Xie, Liangpei Zhang   +5 more
doaj   +1 more source

Discovery of Physics From Data: Universal Laws and Discrepancies

Frontiers in Artificial Intelligence, 2020
Machine learning (ML) and artificial intelligence (AI) algorithms are now being used to automate the discovery of physics principles and governing equations from measurement data alone.
Brian M. de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz   +3 more
doaj   +1 more source

Confidence sets in sparse regression

, 2013
The problem of constructing confidence sets in the high-dimensional linear model with $n$ response variables and $p$ parameters, possibly $p\ge n$, is considered. Full honest adaptive inference is possible if the rate of sparse estimation does not exceed
Nickl, Richard, van de Geer, Sara
core   +1 more source

Locally Sparse Function-on-Function Regression

Journal of Computational and Graphical Statistics, 2022
In functional data analysis, functional linear regression has attracted significant attention recently. Herein, we consider the case where both the response and covariates are functions. There are two available approaches for addressing such a situation: concurrent and nonconcurrent functional models. In the former, the value of the functional response
Mauro Bernardi, Antonio Canale, Marco Stefanucci   +2 more
openaire   +3 more sources

Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim, Han Gil Seo, Roh‐Eul Yoo, Byung‐Mo Oh   +3 more
wiley   +1 more source

Patterns of Postictal Abnormalities in Relation to Status Epilepticus in Adults

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Abnormalities on peri‐ictal diffusion‐weighted magnetic resonance imaging (DWI‐PMAs) are well‐established for patients with status epilepticus (SE), but knowledge on patterns of DWI‐PMAs and their prognostic impact is sparse. Methods This systematic review and individual participant data meta‐analysis included observational studies ...
Andrea Enerstad Bolle, Silvana Sarria‐Estrada, Thomas Bonduelle, Bertram Daniel Dynesen, Manuel Toledo, Zhu Chung Che, Kjell Heuser, Anastasios Chatzikonstantinou, Jérôme Aupy, Udaya Seneviratne, Estevo Santamarina Perez, Christoph Patrick Beier   +11 more
wiley   +1 more source