• KELLEY

  • Referenced in 631 articles [sw04829]
  • pages 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 ... later used to demonstrate the behavior of optimization algorithms. Chapter 7 introduces implicit filtering ... treatment of both, optimization methods for smooth and for noisy functions is a unique feature...
  • Adam

  • Referenced in 892 articles [sw22205]
  • algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates ... stationary objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive ... best known results under the online convex optimization framework. Empirical results demonstrate that Adam works...
  • SNOBFIT

  • Referenced in 24 articles [sw05289]
  • SNOBFIT (Stable Noisy Optimization by Branch and FIT) is a MATLAB 6 package ... robust and fast solution of noisy optimization problems with continuous variables varying within bound, possibly ... taken that the optimization proceeds reasonably even when the interface produces noisy or even occasionally ... experiments, performed with the goal of optimizing some user-specified criterion. Since multiple data points...
  • DiceOptim

  • Referenced in 76 articles [sw07784]
  • package DiceOptim: Kriging-based optimization for computer experiments. Expected Improvement. EGO algorithm. Multipoints ... Liars. Criteria and algorithms for Noisy Kriging-based Optimization , including...
  • subplex

  • Referenced in 25 articles [sw04818]
  • subplex method is well suited for optimizing noisy objective functions. The number of function evaluations ... purpose algorithm well suited for optimization of high-dimensional noisy functions...
  • IMFIL

  • Referenced in 44 articles [sw04814]
  • overview of recent results on optimization of noisy functions, including results that depend...
  • tgp

  • Referenced in 41 articles [sw07921]
  • improvement. The latter supports derivative-free optimization of noisy black-box functions...
  • CoSaMP

  • Referenced in 228 articles [sw08727]
  • approximate a compressible signal from noisy samples. This paper describes a new iterative recovery algorithm ... delivers the same guarantees as the best optimization-based approaches. Moreover, this algorithm offers rigorous...
  • CONDOR

  • Referenced in 24 articles [sw02490]
  • paper CONDOR (COnstrained, Non-linear, Direct, parallel Optimization using trust Region method for high-computing ... field of noisy and high-computing-load objective functions optimization (from 2 min to several...
  • pycma

  • Referenced in 2 articles [sw37047]
  • convex, ill-conditioned, multi-modal, rugged, noisy) optimization problems in continuous search spaces...
  • LocLok

  • Referenced in 2 articles [sw41705]
  • Markov model; (b) it releases the optimal noisy location with the planar isotropic mechanism...
  • HOPSPACK

  • Referenced in 12 articles [sw04187]
  • cores). Optimization problems can be very general: functions can be noisy, nonsmooth and nonconvex, linear ... communities in mind: those who need an optimization problem solved, and those who wish...
  • Noisyopt

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

  • Referenced in 1 article [sw38804]
  • Olympus: A benchmarking framework for noisy optimization and experiment planning. Research challenges encountered across science ... highly time and resource demanding. As optimization algorithms are typically benchmarked on low-dimensional synthetic ... unclear how their performance would translate to noisy, higher-dimensional experimental tasks encountered in chemistry ... easy-to-use framework for benchmarking optimization algorithms against realistic experiments emulated via probabilistic deep...
  • scikit-optimize

  • Referenced in 6 articles [sw37048]
  • noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims...
  • SDBOX

  • Referenced in 30 articles [sw05137]
  • derivative-free algorithm for bound constrained optimization. We propose a new globally convergent derivative-free ... algorithm in the minimization of noisy functions. Finally, we report the results of a preliminary...
  • NOWPAC

  • Referenced in 3 articles [sw08491]
  • provably convergent nonlinear optimizer with path-augmented constraints for noisy regimes. This paper proposes...
  • DFBOX_IMPR

  • Referenced in 22 articles [sw36996]
  • derivative-free algorithm for bound constrained optimization. We propose a new globally convergent derivative-free ... algorithm in the minimization of noisy functions. Finally, we report the results of a preliminary...
  • RBFOpt

  • Referenced in 8 articles [sw28416]
  • method originally proposed by Gutmann (J Glob Optim ... paper are an approach to exploit a noisy but less expensive oracle to accelerate convergence ... automatic model selection phase during the optimization process. Numerical experiments show that RBFOpt is highly...
  • QNSTOP

  • Referenced in 4 articles [sw26832]
  • global optimization, based on an input switch. QNSTOP is particularly effective for “noisy” deterministic problems...