most citedAdaptive sparse group LASSO in quantile regression

21 citations

13 papers

math.CA2026

Asymptotic for orthogonal polynomials with respect to a rational modification of a measure supported on the semi-axis

C. Féliz-Sánchez, H. Pijeira-Cabrera, J. Quintero-Roba

Given a sequence of orthogonal polynomials , orthogonal with respect to a positive Borel measure supported on , let

stat.ME20266 cited

Fast Partial Quantile Regression

Alvaro Mendez Civieta, M. Carmen Aguilera-Morillo, Rosa E. Lillo

Partial least squares (PLS) is a dimensionality reduction technique used as an alternative to ordinary least squares (OLS) in situations where the data is colinear or high dimensio…

stat.ME202621 cited

Adaptive sparse group LASSO in quantile regression

Álvaro Méndez Civieta, M. Carmen Aguilera-Morillo, Rosa E. Lillo

This paper studies the introduction of sparse group LASSO (SGL) to the quantile regression framework. Additionally, a more flexible version, an adaptive SGL is proposed based on th…

cs.CR2026

Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehicles

Marwan Lazrag, Badis Hammi, Lorena Gonzalez-Manzano +1

Poisoning attacks against public datasets lead to major concerns, such as (i) misclassification of perceived objects when the poisoned data is used for training and (ii) embedding…

cs.LG2026

CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat Detection

Diego Cajaraville-Aboy, Marta Moure-Garrido, Carlos Beis-Penedo +5

The use of DNS over HTTPS (DoH) tunneling by an attacker to hide malicious activity within encrypted DNS traffic poses a serious threat to network security, as it allows malicious…

math.OC2026

On leveraging constrained smooth additive regression models for global optimization

Marina Cuesta, Claudia D'Ambrosio, María Durban +2

Many real-world decision-making processes rely on solving mixed-integer nonlinear programs (MINLPs). However, finding high-quality solutions to MINLPs is often computationally dema…