• 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 Non-Convex 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. Shape-constrained 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 long-standing gap between the conventional deterministic ... user-friendly 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]
  • primal-dual interior-point 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.r-project.org...
  • bmrm

  • Referenced in 23 articles [sw11016]
  • methods for minimization of convex and non-convex 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; One-class 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 non-convex 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 convexity-assisted nonconvex optimization, we derive nonasymptotic error...
  • prclust

  • Referenced in 1 article [sw15942]
  • regression-based 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 B-splines and its integral, monotone splines ... splines) and its integral (I-splines), convex splines (C-splines), 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 sparsity-inducing regularizations are ubiquitous in high ... problem at hand. In the context of regression, this can be achieved either by discarding...
  • ADMM-Softmax

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