• Adam

  • Referenced in 948 articles [sw22205]
  • order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order ... best known results under the online convex optimization framework. Empirical results demonstrate that Adam works...
  • JADE

  • Referenced in 146 articles [sw24855]
  • JADE: adaptive differential evolution with optional external archive. A new differential evolution (DE) algorithm, JADE ... proposed to improve optimization performance by implementing a new mutation strategy ”DE/current-to-pbest” with optional external ... archive and updating control parameters in an adaptive manner. The DE/current-to- pbest is a generalization ... other classic or adaptive DE algorithms, the canonical particle swarm optimization, and other evolutionary algorithms...
  • AdaGrad

  • Referenced in 166 articles [sw22202]
  • adaptive gradient algorithm; Adaptive subgradient methods for online learning and stochastic optimization. We present ... more informative gradient-based learning. Metaphorically, the adaptation allows us to find needles in haystacks ... paradigm stems from recent advances in stochastic optimization and online learning which employ proximal functions ... describe and analyze an apparatus for adaptively modifying the proximal function, which significantly simplifies setting...
  • Tabu search

  • Referenced in 1079 articles [sw08556]
  • tabu search is the ability to adapt a rudimentary prototype implementation to encompass additional model ... sophistication. We provide several examples of discrete optimization problems to illustrate the strategic concerns...
  • NOMAD

  • Referenced in 108 articles [sw02916]
  • implements the Mesh Adaptive Direct Search (MADS) algorithm for blackbox optimization under general nonlinear constraints...
  • ISOLATE

  • Referenced in 221 articles [sw07741]
  • algorithm is presented, which is optimal in terms of memory usage and as fast ... From this new algorithm, we derive an adaptive semi-numerical version, using multi-precision interval ... arithmetic. We finally show that these critical optimizations have important consequences since our new algorithm...
  • CMA-ES

  • Referenced in 124 articles [sw05063]
  • Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization ... linear or non-convex continuous optimization problems. They belong to the class of evolutionary algorithms ... covariance matrix. The covariance matrix adaptation (CMA) is a method to update the covariance matrix ... function f is ill-conditioned. Adaptation of the covariance matrix amounts to learning a second...
  • PLTMG

  • Referenced in 217 articles [sw00717]
  • triangular finite elements. PLTMG features options for adaptive h, p, and hp refinement, coarsening ... provides options for solving several classes of optimal control and obstacle problems. The package includes ... packages. Support for the Bank-Holst parallel adaptive meshing paradigm and corresponding domain decomposition solver...
  • simannf90

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

  • Referenced in 28 articles [sw20162]
  • Flow* supports a wide variety of optimizations including adaptive step sizes, adaptive selection of approximation...
  • HyperLogLog

  • Referenced in 22 articles [sw02063]
  • only 1.5 kilobytes. The algorithm parallelizes optimally and adapts to the sliding window model...
  • AbYSS

  • Referenced in 22 articles [sw09881]
  • AbYSS: Adapting Scatter Search to Multiobjective Optimization. We propose ... algorithm to solve multiobjective optimization problems. Our proposal adapts the well-known scatter search template...
  • Hyperband

  • Referenced in 20 articles [sw41120]
  • hyperparameters. While recent approaches use Bayesian optimization to adaptively select configurations, we focus on speeding ... search through adaptive resource allocation and early-stopping. We formulate hyperparameter optimization as a pure...
  • CppAD

  • Referenced in 37 articles [sw04866]
  • Benders decompositions, and multilevel optimization. In this paper we adapt a known automatic differentiation ... implicitly defined functions for application to optimal value functions. The formulation we develop is well...
  • CMARS

  • Referenced in 31 articles [sw08523]
  • nonparametric regression with multivariate adaptive regression splines supported by continuous optimization Regression analysis ... method for modelling relationships between variables. Multivariate adaptive regression splines (MARS) especially is very useful ... regularization problem, and treat this with continuous optimization technique, in particular, the framework of conic...
  • HypE

  • Referenced in 88 articles [sw19794]
  • hypervolume estimation algorithm for multi-objective optimization, by which the accuracy of the estimates ... also the runtime can be flexibly adapted. Moreover, we show how the same principle ... compare the outcomes of different multi-objective optimizers with respect to the hypervolume...
  • AIR tools

  • Referenced in 97 articles [sw09203]
  • relaxation parameter can be fixed, or chosen adaptively in each iteration; in the former case ... training” algorithm that finds the optimal parameter for a given test problem. The stopping rules...
  • alabama

  • Referenced in 15 articles [sw09332]
  • package alabama: Constrained nonlinear optimization. Augmented Lagrangian Adaptive Barrier Minimization Algorithm for optimizing smooth nonlinear...
  • hgam

  • Referenced in 73 articles [sw11201]
  • optimality of our estimator for high dimensional but sparse additive models. Finally, an adaptive version...
  • qLearn

  • Referenced in 20 articles [sw11117]
  • Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap scheme ... history. A common method for estimating an optimal dynamic treatment regime from data ... parameters indexing the optimal dynamic regime. We propose an adaptive choice of m and show...