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osqp
osqp:Quadratic Programming Solver using the 'OSQP' Library
Provides bindings to the 'OSQP' solver. The 'OSQP' solver is a numerical optimization package or solving convex quadratic programs written in 'C' and based on the alternating direction method of multipliers. See <doi:10.48550/arXiv.1711.08013> for details.
Maintained by Balasubramanian Narasimhan. Last updated 10 months ago.
admmconvex-optimizationlassomachine-learningoperator-splittingquadratic-programmingcpp
12 stars 8.21 score 47 scripts 65 dependents
chikuang
SLSEdesign:Optimal Regression Design under the Second-Order Least Squares Estimator
With given inputs that include number of points, discrete design space, a measure of skewness, models and parameter value, this package calculates the objective value, optimal designs and plot the equivalence theory under A- and D-optimal criteria under the second-order Least squares estimator. This package is based on the paper "Properties of optimal regression designs under the second-order least squares estimator" by Chi-Kuang Yeh and Julie Zhou (2021) <doi:10.1007/s00362-018-01076-6>.
Maintained by Chi-Kuang Yeh. Last updated 6 months ago.
convex-optimizationcvxdesign-of-experimentsleast-squaresoptimal-designs
4.54 score 2 scripts
pievos101
TopKSignal:A Convex Optimization Tool for Signal Reconstruction from Multiple Ranked Lists
A mathematical optimization procedure in combination with statistical bootstrap for the estimation of the latent signals (sometimes called scores) informing the global consensus ranking (often named aggregation ranking). To solve mid/large-scale problems, users should install the 'gurobi' optimiser (available from <https://www.gurobi.com/>).
Maintained by Bastian Pfeifer Maintainer. Last updated 1 years ago.
convex-optimizationranking-datasignal-estimation
3 stars 4.18 score 1 scripts