• KELLEY

  • Referenced in 631 articles [sw04829]
  • also second order derivatives of the objective function. The first part contains five chapters ... long, deals with the optimization of noisy functions. Such optimization problems arise, e.g., when ... first chapter provides a discussion of noisy functions, basics concepts, and three simple examples that ... optimization methods for smooth and for noisy functions is a unique feature of this book...
  • IMFIL

  • Referenced in 44 articles [sw04814]
  • methods that use interpolation to reconstruct the function and its higher derivatives, implicit filtering builds ... recent results on optimization of noisy functions, including results that depend on non-smooth analysis...
  • Adam

  • Referenced in 861 articles [sw22205]
  • order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order ... stationary objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive...
  • subplex

  • Referenced in 25 articles [sw04818]
  • unconstrained optimization of general multivariate functions. Like the Nelder-Mead simplex method it generalizes ... method is well suited for optimizing noisy objective functions. The number of function evaluations required ... Rowan for his Ph.D. Thesis: Functional Stability Analysis of Numerical Algorithms (University of Texas ... suited for optimization of high-dimensional noisy functions...
  • SDBOX

  • Referenced in 30 articles [sw05137]
  • produces an improvement of the objective function value. We also derive a bound ... algorithm in the minimization of noisy functions. Finally, we report the results of a preliminary...
  • SuLQ

  • Referenced in 128 articles [sw11355]
  • database and f is a function mapping database rows to {0, 1}. The true answer ... ΣiεS f(di), and a noisy version is released as the response to the query ... rows. We call this query and (slightly) noisy reply the SuLQ (Sub-Linear Queries) primitive ... modify the privacy analysis to real-valued functions f and arbitrary row types...
  • DFBOX_IMPR

  • Referenced in 22 articles [sw36996]
  • produces an improvement of the objective function value. We also derive a bound ... algorithm in the minimization of noisy functions. Finally, we report the results of a preliminary...
  • tgp

  • Referenced in 41 articles [sw07921]
  • supported. Sequential experimental design and adaptive sampling functions are also provided, including ... supports derivative-free optimization of noisy black-box functions...
  • CONDOR

  • Referenced in 24 articles [sw02490]
  • trust Region method for high-computing load function). The experimental results are very encouraging ... field of noisy and high-computing-load objective functions optimization (from 2 min to several...
  • HOPSPACK

  • Referenced in 12 articles [sw04187]
  • problems can be very general: functions can be noisy, nonsmooth and nonconvex, linear and nonlinear...
  • GeNIe

  • Referenced in 7 articles [sw13964]
  • GeNie Modeler implements multi-attribute utility functions, Noisy-OR and Noisy-AND gates, value...
  • L2WPMA

  • Referenced in 9 articles [sw04326]
  • turning points of a function from some noisy measurements of its values, or in image...
  • SNOBFIT

  • Referenced in 24 articles [sw05289]
  • robust and fast solution of noisy optimization problems with continuous variables varying within bound, possibly ... constraints. Discrete variables are not supported. Objective function values must be provided by a file ... proceeds reasonably even when the interface produces noisy or even occasionally undefined results (hidden constraints ... entered, SNOBFIT can take advantage of parallel function evaluations. The method combines a branching strategy...
  • noisyCE2

  • Referenced in 1 article [sw42092]
  • package noisyCE2: Cross-Entropy Optimisation of Noisy Functions. Cross-Entropy optimisation of unconstrained deterministic ... noisy functions illustrated in Rubinstein and Kroese (2004, ISBN: 978-1-4419-1940-3) through...
  • scikit-optimize

  • Referenced in 6 articles [sw37048]
  • minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model...
  • KrigInv

  • Referenced in 13 articles [sw15933]
  • KrigInv: Kriging-based Inversion for Deterministic and Noisy Computer Experiments. Criteria and algorithms for sequentially ... estimating level sets of a multivariate numerical function, possibly observed with noise...
  • Noisyopt

  • Referenced in 1 article [sw32790]
  • Noisyopt: A python library for optimizing noisy functions. In some optimization problems a precise evaluation ... provides algorithms to optimize a function based on noisy evaluations. Currently the following algorithms ... explicitely calculate the gradient of the function...
  • clusterGeneration

  • Referenced in 16 articles [sw23400]
  • visualize clusters. The package also contains a function to generate random clusters based on factorial ... clusters, number of variables, number of noisy variables...
  • denoiseR

  • Referenced in 7 articles [sw17854]
  • rank matrix from noisy data using singular values thresholding and shrinking functions. Impute missing values...
  • RBoost

  • Referenced in 3 articles [sw29975]
  • Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners. AdaBoost ... However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving ... noisy data of AdaBoost stems from the exponential loss function, which puts unrestricted penalties ... noisy data compared with AdaBoost. RBoost1 and RBoost2 optimize a nonconvex loss function...