
ARGONAUT
 Referenced in 5 articles
[sw20651]
 incorporates variable selection, bounds tightening and constrained sampling techniques, in order to develop accurate surrogate ... large set of test problems for constrained global optimization with a large number of input...

BayesTree
 Referenced in 59 articles
[sw07995]
 trees” model where each tree is constrained by a regularization prior to be a weak ... iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively, BART...

CONMIN
 Referenced in 50 articles
[sw04741]
 intended primarily for efficient solution of constrained problems, unconstrained function minimization problems may also ... used without special knowledge of optimization techniques. Sample problems are inc! luded to help...

ibr
 Referenced in 7 articles
[sw11227]
 sample predictive capabilities than the underlying base smoother, or competing structurally constrained models (MARS ... small dimension (3≤d≤7) and moderate sample size n≤1000. Moreover our estimator ... fully nonparametric regression estimator is available without constrained assumption such as additivity for example ... Data, our method reduces the out of sample prediction error by 20%. An R package...

PyMix
 Referenced in 2 articles
[sw07781]
 parameter learning; Parameter estimation for pairwise constrained samples...

DYANA
 Referenced in 11 articles
[sw08628]
 have good sampling properties for calculating protein structures that are wellconstrained by experimental...

SDPEN
 Referenced in 17 articles
[sw05152]
 Sequential penalty derivativefree methods for nonlinear constrained optimization. We consider the problem of minimizing ... minimization procedure must use only a suitable sampling of the problem functions. These problems arise ... theoretical result regarding the connections between the sampling technique and the updating of the penalization ... guarantee convergence to stationary points of the constrained problem. On the basis of the general...

TLS
 Referenced in 1 article
[sw29784]
 optimized period sampling and transit duration sampling, constrained to the physically plausible range. A typical...

IMFIL
 Referenced in 40 articles
[sw04814]
 filtering is a way to solve boundconstrained optimization problems for which derivative information ... area of derivativefree or sampling methods to be accompanied by publicly available software...

GerryChain
 Referenced in 1 article
[sw35963]
 plans for comparison. Usually, we will constrain these sampled plans in such a way that...

TEXPLORE
 Referenced in 7 articles
[sw13721]
 difference reinforcement learning for robots and timeconstrained domains This book presents and develops ... must learn in very few samples; 2) it must learn in domains with continuous state ... particular, this book is focused on timeconstrained domains where the first challenge is critically ... must learn in very few samples...

COSMICS
 Referenced in 2 articles
[sw16654]
 matter power spectra and produces constrained or unconstrained samples of the matter density field. Version...

SDBOX
 Referenced in 27 articles
[sw05137]
 SDBOX: A derivativefree algorithm for bound constrained optimization. We propose a new globally convergent ... objective function on the feasible set by sampling it along the coordinate directions. Whenever...

BayesianPower
 Referenced in 1 article
[sw37923]
 package BayesianPower: Sample Size and Power for Comparing Inequality Constrained Hypotheses. A collection of methods ... determine the required sample size for the evaluation of inequality constrained hypotheses by means...

xsample
 Referenced in 1 article
[sw37323]
 MCMC) algorithms to uniformly sample the feasible region of constrained linear problems. Two existing...

DFBOX_IMPR
 Referenced in 18 articles
[sw36996]
 IMPR: A derivativefree algorithm for bound constrained optimization. We propose a new globally convergent ... objective function on the feasible set by sampling it along the coordinate directions. Whenever...

Nway Toolbox
 Referenced in 30 articles
[sw12996]
 function (including MILES); Predicting scores for new samples using a given model; Predicting the dependent ... data analysis, indafac for PARAFAC, PARALIND for constrained PARAFAC models, jackknifing for PARAFAC...

PowerUpR
 Referenced in 0 articles
[sw17533]
 sample size (MRSS), functions to solve constrained optimal sample allocation (COSA) problems, and to visualize...

SDMINMAX
 Referenced in 12 articles
[sw36992]
 derivativefree algorithm for linearly constrained finite minimax problems. Due to the nonsmoothness of this ... proposed method is based on a sampling of the smooth function along a suitable search...

TRIOPT
 Referenced in 6 articles
[sw02486]
 algorithm, TRIOPT, for solving lowdimensional boundconstrained black box global optimization problems. The method ... Delaunay triangulation of a given set of samples in the feasible domain, and then...