• BayesOpt

  • Referenced in 6 articles [sw12003]
  • Bayesian optimization methods to solve nonlinear optimization, stochastic bandits or sequential experimental design problems. Bayesian...
  • GOP

  • Referenced in 6 articles [sw17432]
  • search method to improve the initialization of optimization algorithms. We introduce a novel metaheuristic methodology ... initialization of a given deterministic or stochastic optimization algorithm. Our objective is to improve...
  • COMPASS

  • Referenced in 37 articles [sw03040]
  • simulation using COMPASS. We propose an optimization-via-simulation algorithm, called COMPASS, for use when ... performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables ... COMPASS converges to the set of local optimal solutions with probability 1 for both terminating...
  • QNSTOP

  • Referenced in 3 articles [sw26832]
  • QNSTOP Quasi-Newton Algorithm for Stochastic Optimization. QNSTOP consists of serial and parallel (OpenMP) Fortran ... codes for the quasi-Newton stochastic optimization method of Castle and Trosset. For stochastic problems ... driver subroutine can be used for stochastic optimization or deterministic global optimization, based...
  • SGDLibrary

  • Referenced in 3 articles [sw26680]
  • SGDLibrary: a MATLAB library for stochastic optimization algorithms. We consider the problem of finding ... scale data is to use a stochastic optimization algorithm to solve the problem. SGDLibrary ... MATLAB library of a collection of stochastic optimization algorithms. The purpose of the library...
  • SpectralNet

  • Referenced in 3 articles [sw26162]
  • using a procedure that involves constrained stochastic optimization. Stochastic optimization allows it to scale...
  • R-MAX

  • Referenced in 32 articles [sw02539]
  • environment and acts based on the optimal policy derived from this model. The model ... algorithm, covering zero-sum stochastic games. (2) It has a built-in mechanism for resolving ... exploitation dilemma. (3) It formally justifies the “optimism under uncertainty” bias used in many ... algorithm for learning in single controller stochastic games. (5) It generalizes the algorithm by Monderer...
  • Acacia+

  • Referenced in 13 articles [sw25260]
  • feature: the synthesis of the optimal strategy in a stochastic environment among...
  • SOCSol4L

  • Referenced in 2 articles [sw15008]
  • solution to a continuous-time stochastic optimal control problem. Computing the solution to a stochastic ... optimal control problem is difficult. A method of approximating ... solution to a given continuous-time stochastic optimal control problem using Markov chains was developed...
  • Genetic Algorithm and Direct Search Toolbox

  • Referenced in 29 articles [sw13052]
  • that are difficult to solve with traditional optimization techniques, including problems that are not well ... objective function is discontinuous, highly nonlinear, stochastic, or has unreliable or undefined derivatives. The Genetic ... Algorithm and Direct Search Toolbox complements other optimization methods to help you find good starting...
  • COPASI

  • Referenced in 63 articles [sw12253]
  • their behavior using ODEs or Gillespie’s stochastic simulation algorithm; arbitrary discrete events ... extensive support for parameter estimation and optimization. COPASI provides means to visualize data in customizable...
  • SDDP

  • Referenced in 2 articles [sw27099]
  • package for solving large multistage convex stochastic optimization problems using stochastic dual dynamic programming ... reasonable amount of background knowledge about stochastic optimization, the SDDP algorithm, Julia, and JuMP...
  • PRISM-games

  • Referenced in 16 articles [sw12934]
  • checking algorithms for stochastic games, as well as functionality to synthesise optimal player strategies, explore...
  • CYCLADES

  • Referenced in 3 articles [sw15227]
  • CYCLADES, a general framework for parallelizing stochastic optimization algorithms in a shared memory setting. CYCLADES...
  • onlinePCA

  • Referenced in 3 articles [sw21315]
  • namely, perturbation techniques, incremental methods, and stochastic optimization, and compare their statistical accuracy, computation time...
  • DSCOVR

  • Referenced in 5 articles [sw28397]
  • this paper, we focus on distributed optimization of large linear models with convex loss functions ... exploit its structure by doubly stochastic coordinate optimization with variance reduction (DSCOVR). Compared with other...
  • HYPENS

  • Referenced in 4 articles [sw00422]
  • already defined in Matlab, such as optimization routines, stochastic functions, matrices and arrays ... programs and be used for analysis and optimization via simulation. The large set of plot...
  • HOGWILD

  • Referenced in 53 articles [sw28396]
  • Free Approach to Parallelizing Stochastic Gradient Descent. Stochastic Gradient Descent (SGD) is a popular algorithm ... work. We show that when the associated optimization problem is sparse, meaning most gradient updates...
  • SQG

  • Referenced in 19 articles [sw00907]
  • complementary set of methods called stochastic quasi-gradient methods (SQG). These methods are specifically designed ... continuous distributions of random parameters and nonlinear optimization problems. They are suited for optimization ... such methods consists of multiperiod dynamic stochastic models with parametrized decision rules. Supply chain management...
  • InfSOCSol

  • Referenced in 1 article [sw08392]
  • continuous-time in nite horizon stochastic optimal control problem. This paper describes a suite ... optimal solution to an infinite-horizon stochastic optimal control problem. The suite is an updated...