• Adam

  • Referenced in 892 articles [sw22205]
  • Adam: A Method for Stochastic Optimization. We introduce Adam, an algorithm for first-order gradient ... stochastic objective functions, based on adaptive estimates of lower-order moments. The method is straightforward ... terms of data and/or parameters. The method is also appropriate for non-stationary objectives ... practice and compares favorably to other stochastic optimization methods. Finally, we discuss AdaMax, a variant...
  • AdaGrad

  • Referenced in 166 articles [sw22202]
  • gradient algorithm; Adaptive subgradient methods for online learning and stochastic optimization. We present ... family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed ... paradigm stems from recent advances in stochastic optimization and online learning which employ proximal functions ... theoretical analysis and show that adaptive subgradient methods outperform state...
  • ALEA

  • Referenced in 60 articles [sw10167]
  • lies on: generalised polynomial chaos (gpc) methods; stochastic Galerkin FEM; adaptive numerical methods; tensor methods...
  • DAKOTA

  • Referenced in 77 articles [sw05202]
  • uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares...
  • CMA-ES

  • Referenced in 121 articles [sw05063]
  • Strategy. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear ... generated by variation, usually in a stochastic way, and then some individuals are selected ... covariance matrix adaptation (CMA) is a method to update the covariance matrix of this distribution...
  • Pegasos

  • Referenced in 103 articles [sw08752]
  • contrast, previous analyses of stochastic gradient descent methods for SVMs require Ω(1/ϵ2) iterations...
  • S-ROCK

  • Referenced in 42 articles [sw11792]
  • ROCK: Chebyshev methods for stiff stochastic differential equations. We present and analyze a new class ... solution of stiff stochastic differential equations (SDEs). These methods, called S-ROCK (for stochastic orthogonal ... than the standard explicit methods proposed so far for stochastic problems and give significant speed...
  • Kiva-2

  • Referenced in 66 articles [sw08987]
  • chemical reactions are allowed. A stochastic particle method is used to calculate evaporating liquid sprays...
  • MLMSRBF

  • Referenced in 43 articles [sw07571]
  • stochastic radial basis function method for the global optimization of expensive functions We introduce ... derivatives are unavailable. The proposed Stochastic Response Surface (SRS) Method iteratively utilizes a response surface...
  • ADADELTA

  • Referenced in 59 articles [sw39429]
  • method for gradient descent called ADADELTA. The method dynamically adapts over time using only first ... minimal computational overhead beyond vanilla stochastic gradient descent. The method requires no manual tuning...
  • MCQueue

  • Referenced in 148 articles [sw05198]
  • methods discussed in the book H.C. Tijms, A First Course in Stochastic Models, Wiley...
  • mirt

  • Referenced in 36 articles [sw13479]
  • estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses...
  • gss

  • Referenced in 293 articles [sw06099]
  • spline ANOVA models Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been ... ample desktop and laptop computing power, smoothing methods are now finding their ways into everyday...
  • SSS

  • Referenced in 34 articles [sw07794]
  • Shotgun stochastic search for “Large p” regression Model search in regression with very large numbers ... MCMC) methods are often infeasible or ineffective. We describe a novel shotgun stochastic search ... cancer genomics, comparisons with MCMC and other methods, and theoretical and simulation-based aspects...
  • SQG

  • Referenced in 19 articles [sw00907]
  • implementation of a complementary set of methods called stochastic quasi-gradient methods (SQG). These methods ... application area of such methods consists of multiperiod dynamic stochastic models with parametrized decision rules...
  • KIVA-4

  • Referenced in 25 articles [sw02561]
  • chemical reactions are allowed. A stochastic particle method is used to calculate evaporating liquid sprays...
  • Benchmarking

  • Referenced in 26 articles [sw14630]
  • There is also support comparative methods based on Stochastic Frontier Analyses (SFA). In general...
  • CCLS

  • Referenced in 20 articles [sw36049]
  • large, which calls for efficient approximate methods, mainly stochastic local search (SLS) ones. However...
  • COSSAN

  • Referenced in 10 articles [sw16555]
  • covers a fairly wide field of stochastic methods including various sampling techniques, random fields, fatigue ... considering uncertainties and consequently perform stochastic analyses using methods based on Monte Carlo procedures...
  • StOpt

  • Referenced in 10 articles [sw32903]
  • providing tools in C++ for solving some stochastic optimization problems encountered in finance ... following some uncontrolled Stochastic Differential Equations (python binding provided). Semi-Lagrangian methods for Hamilton Jacobi ... Stochastic Differential Equations (C++ only). Stochastic Dual Dynamic Programming methods to deal with stochastic stocks ... where the underlying stochastic state is controlled. Some pure Monte Carlo Methods are proposed...