
KNITRO
 Referenced in 200 articles
[sw00490]
 problems, both convex and nonconvex. It is also effective for nonlinear regression, problems with complementarity...

QICD
 Referenced in 20 articles
[sw19679]
 Estimate the Coefficients for NonConvex Penalized Quantile Regression Model by using QICD Algorithm. Extremely...

fdrtool
 Referenced in 34 articles
[sw08196]
 regression and antitonic regression with weights), for computing the greatest convex minorant...

REBayes
 Referenced in 13 articles
[sw20967]
 some other density estimation and regression methods based on convex optimization...

pyStoNED
 Referenced in 1 article
[sw40063]
 pyStoNED: A Python Package for Convex Regression and Frontier Estimation. Shapeconstrained nonparametric regression ... analysis, recent developments in the multivariate convex regression and related techniques such as convex quantile ... regression and convex expectile regression have bridged the longstanding gap between the conventional deterministic ... userfriendly tool for the multivariate convex regression, convex quantile regression, convex expectile regression, isotonic...

ARock
 Referenced in 32 articles
[sw16800]
 special cases of ARock for linear systems, convex optimization, and machine learning, as well ... consensus problems. Numerical experiments solving sparse logistic regression problems are presented...

scar
 Referenced in 20 articles
[sw31377]
 estimator of the generalised additive and index regression with shape constraints. Each additive component function ... nine possible shape restrictions: linear, increasing, decreasing, convex, convex increasing, convex decreasing, concave, concave increasing...

OOQP
 Referenced in 40 articles
[sw04743]
 primaldual interiorpoint method, for solving convex quadratic programming problems (QPs). It contains code ... arising from support vector machines, Huber regression problems, and QPs with bound constraints. OOQP also...

COBRA
 Referenced in 9 articles
[sw14858]
 regression function is introduced. Instead of building a linear or convex optimized combination over ... companion R package called (standing for COmBined Regression Alternative) is presented (downloadable on http://cran.rproject.org...

bmrm
 Referenced in 23 articles
[sw11016]
 methods for minimization of convex and nonconvex risk under L1 or L2 regularization. Implements ... beta optimization, ROC optimization, ordinal regression, quantile regression, epsilon insensitive regression, least mean square, logistic...

MeLOn
 Referenced in 2 articles
[sw40846]
 Support vector machine for regression; Oneclass support vector classification; Convex hull of point cloud...

QPBB
 Referenced in 2 articles
[sw31774]
 instrumental variable quantile regression (IVQR). We model IVQR as a convex quadratic program with complementarity...

ActiveClean
 Referenced in 1 article
[sw37880]
 class of models called convex loss models (e.g., linear regression and SVMs), and prioritizes cleaning...

bst
 Referenced in 1 article
[sw25766]
 convex and nonconvex loss functions, for both classical and robust regression and classification problems...

SOFAR
 Referenced in 7 articles
[sw31665]
 suggest the method of sparse orthogonal factor regression (SOFAR) via the sparse singular value decomposition ... vector autoregression analysis. Exploiting the framework of convexityassisted nonconvex optimization, we derive nonasymptotic error...

prclust
 Referenced in 1 article
[sw15942]
 regressionbased clustering (PRclust). One algorithm is based on quadratic penalty and difference convex method...

splines2
 Referenced in 2 articles
[sw32945]
 package splines2: Regression Spline Functions and Classes. Constructs Bsplines and its integral, monotone splines ... splines) and its integral (Isplines), convex splines (Csplines), and their derivatives of given...

KLERC
 Referenced in 1 article
[sw37381]
 regression (SVER). This paper reformulates the Lagrangian function of SVER as a differentiable convex function...

Celer
 Referenced in 5 articles
[sw37123]
 Solver for the Lasso with Dual Extrapolation. Convex sparsityinducing regularizations are ubiquitous in high ... problem at hand. In the context of regression, this can be achieved either by discarding...

ADMMSoftmax
 Referenced in 4 articles
[sw32744]
 multipliers (ADMM) for solving multinomial logistic regression (MLR) problems. Our method is geared toward supervised ... independent smallscale smooth, convex problems, and a trivial dual variable update. The solution...