• GRASP

  • Referenced in 133 articles [sw01094]
  • Algorithm 754: Fortran subroutines for approximate solution of dense ... quadratic assignment problems using GRASP (greedy randomized adaptive search procedures...
  • simannf90

  • Referenced in 120 articles [sw05059]
  • optimization. The algorithm is essentially an iterative random search procedure with adaptive moves along...
  • BartPy

  • Referenced in 99 articles [sw40584]
  • accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively ... dimensionally adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms...
  • BayesTree

  • Referenced in 64 articles [sw07995]
  • accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively ... dimensionally adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms...
  • MSLiP

  • Referenced in 111 articles [sw01410]
  • efficient implementation of a nested decomposition algorithm for the multistage stochastic linear programming problem. Many ... tricks developed for deterministic staircase problems are adapted to the stochastic setting and their effect ... random structures for the input data. Numerical results compare the performance of the algorithm...
  • T-IFISS

  • Referenced in 13 articles [sw23889]
  • Efficient adaptive algorithms for elliptic PDEs with random data. We present a novel adaptive algorithm ... elliptic PDE problems with correlated random data. The algorithm employs a hierarchical a posteriori error ... used in the algorithm to perform a balanced adaptive refinement of spatial and parametric components ... efficiency of the algorithm for three representative PDEs with random coefficients are reported. The software...
  • ramcmc

  • Referenced in 22 articles [sw17890]
  • Robust Adaptive Metropolis Algorithm. Function for adapting the shape of the random walk Metropolis proposal...
  • Krill herd

  • Referenced in 53 articles [sw25670]
  • proposed for solving optimization tasks. The KH algorithm is based on the simulation ... random diffusion. For more precise modeling of the krill behavior, two adaptive genetic operators ... added to the algorithm. The proposed method is verified using several benchmark problems commonly used...
  • Quicksort

  • Referenced in 185 articles [sw20694]
  • most programming libraries. Some sorting algorithms are adaptive, i.e., they have a complexity analysis that ... actual running time of Quicksort is adaptive with respect to the presortedness measure Inv. Differences ... value. We then show that for the randomized version of Quicksort, the number of element...
  • PROC NLMIXED

  • Referenced in 70 articles [sw11039]
  • random effects. Different integral approximations are available, the principal ones being adaptive Gaussian quadrature ... default is a dual quasi-Newton algorithm. Successful convergence of the optimization problem results ... using empirical Bayes estimates of the random effects. You can also estimate arbitrary functions...
  • GLLAMM

  • Referenced in 63 articles [sw06517]
  • Newton Raphson Algorithm (ml with method d0). In the case of discrete random effects ... random effects or factors. Two methods are available for numerical integration: Quadrature or adaptive quadrature...
  • Grapham

  • Referenced in 5 articles [sw08541]
  • Grapham: graphical models with adaptive random walk Metropolis algorithms. Recently developed adaptive Markov chain Monte...
  • Miniball

  • Referenced in 44 articles [sw05179]
  • show that Welzl’s randomized linear-time algorithm for computing the ball spanned ... work for balls. Consequently, the existing adaptations of the method to the ball case...
  • ACRS

  • Referenced in 6 articles [sw05052]
  • optimization. ARCS: A Derivative-Free Adaptively Controlled Random Search algorithm for bound constrained global optimization...
  • Borg

  • Referenced in 11 articles [sw08873]
  • Auto-Adaptive Many-Objective Evolutionary. This study introduces the Borg multi-objective evolutionary algorithm (MOEA ... convergence speed named -progress, randomized restarts, and auto-adaptive multioperator recombination into a unified optimization ... replicate random seed trials. The Borg MOEA is not a single algorithm; instead ... represents a class of algorithms whose operators are adaptively selected based on the problem...
  • Hyperband

  • Referenced in 20 articles [sw41120]
  • hyperparameter optimization. Performance of machine learning algorithms depends critically on identifying a good ... Bayesian optimization to adaptively select configurations, we focus on speeding up random search through adaptive ... allocated to randomly sampled configurations. We introduce a novel algorithm, Hyperband, for this framework...
  • Algorithm 787

  • Referenced in 11 articles [sw13182]
  • Algorithm 787: Fortran subroutines for approximate solution of maximum independent set problems using GRASP ... Greedy Randomized Adaptive Search Procedure (GRASP) is used to produce the solutions. The algorithm...
  • KADABRA

  • Referenced in 4 articles [sw25810]
  • KADABRA is an adaptive algorithm for betweenness via random approximation. We present KADABRA ... most algorithms that approximate betweenness centrality. We show that, on realistic random graph models ... rigorous application of the adaptive sampling technique. This approach decreases the total number of shortest...
  • TABARIS

  • Referenced in 16 articles [sw02534]
  • subgraph. These are obtained by applying an adaptation of Tabu Search. Computational results are given ... Tabu Search a competitive algorithm is obtained; the case of randomly generated graphs having...
  • GOP

  • Referenced in 6 articles [sw17432]
  • those obtained with the core optimization algorithms alone and with two additional global optimization methods ... Direct Tabu Search and Continuous Greedy Randomized Adaptive Search). These latter also aim at improving ... initial condition for the core algorithms. The numerical results seem to indicate that our approach...