Results 261 to 270 of about 163,423 (274)

Variable selection in convex quantile regression: L1-norm or L0-norm regularization?

European Journal of Operational Research, 2023
Sheng Dai
exaly  

A study on comparison of convex and non-convex penalized regression methods

2023
In linear regression, penalized regression methods are used to obtain more accurate predictions depending on the structure of the data set. In addition, it is possible to determine the explanatory variables associated with the response variable by using penalized regression methods. In this study, the performances of ridge, LASSO, elastic net, adaptive
openaire   +1 more source

Shadow prices and marginal abatement costs: Convex quantile regression approach

European Journal of Operational Research, 2021
Timo Kuosmanen, Xun Zhou
exaly  

A Smoothing Proximal Gradient Algorithm for Nonsmooth Convex Regression with Cardinality Penalty

SIAM Journal on Numerical Analysis, 2020
Wei Bian, Xiaojun Chen
exaly  

A Computational Framework for Multivariate Convex Regression and Its Variants

Journal of the American Statistical Association, 2019
Rahul Mazumder, Bodhisattva Sen
exaly  

Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach

IEEE Transactions on Information Theory, 2013
Yaniv Plan, Roman Vershynin
exaly  

Training Lagrangian twin support vector regression via unconstrained convex minimization

Knowledge-Based Systems, 2014
Deepak Gupta
exaly  

Robust non-convex least squares loss function for regression with outliers

Knowledge-Based Systems, 2014
Kuaini Wang, Ping Zhong
exaly  

Real-time fuzzy regression analysis: A convex hull approach

European Journal of Operational Research, 2011
Azizul Azhar Ramli, Junzo Watada, Witold Pedrycz   +2 more
exaly  

Spontaneous Regression of Cancer

Ca-A Cancer Journal for Clinicians, 1974
exaly