• 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 well-constrained by experimental...
  • SDPEN

  • Referenced in 17 articles [sw05152]
  • Sequential penalty derivative-free 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 bound-constrained optimization problems for which derivative information ... area of derivative-free 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 time-constrained 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 time-constrained 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 derivative-free 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 derivative-free 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...
  • N-way 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]
  • derivative-free 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 low-dimensional bound-constrained black box global optimization problems. The method ... Delaunay triangulation of a given set of samples in the feasible domain, and then...