• GradSamp

  • Referenced in 82 articles [sw05270]
  • robust gradient sampling algorithm for nonsmooth, nonconvex optimization The authors describe a practical and robust ... only request formulated is that the gradient of the function is easily computed where...
  • HIFOO

  • Referenced in 45 articles [sw05188]
  • based on quasi-Newton updating and gradient sampling...
  • HANSO

  • Referenced in 9 articles [sw05271]
  • package based on the BFGS and gradient sampling methods. For general unconstrained minimization: convex ... including BFGS, limited memory BFGS and gradient sampling methods, based on weak Wolfe line search...
  • DAKOTA

  • Referenced in 50 articles [sw05202]
  • optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion...
  • SLQP-GS

  • Referenced in 5 articles [sw05162]
  • Sequential Linear or Quadratic Programming with Gradient Sampling (Matlab...
  • CONMIN

  • Referenced in 50 articles [sw04741]
  • provide gradient information. If analytic gradients of the objective or constraint functions are not available ... used without special knowledge of optimization techniques. Sample problems are inc! luded to help...
  • IMFIL

  • Referenced in 26 articles [sw04814]
  • interpolates to get an approximation of the gradient. Implicit Filtering describes the algorithm, its convergence ... area of derivative-free or sampling methods to be accompanied by publicly available software...
  • GPDT

  • Referenced in 40 articles [sw04803]
  • such as the quadratic subproblem solution, the gradient updating, the working set selection, are systematically ... real-world data sets with millions training samples highlight how the software makes large scale...
  • ABCRATE

  • Referenced in 2 articles [sw00011]
  • potential energy and its gradient at that geometry (sample subprograms for several systems are provided...
  • IJK

  • Referenced in 1 article [sw21790]
  • dual contouring and Religrad for computing reliable gradients from scalar data. It also contains programs ... information, for generating regular grid samplings of scalar and gradient fields, for measuring the angle...
  • NESVM

  • Referenced in 5 articles [sw08753]
  • NESVM: A Fast Gradient Method for Support Vector Machines. Support vector machines (SVMs) are invaluable ... applications with a great deal of samples as well as a large number of features ... paper, thus, we present NESVM, a fast gradient SVM solver that can optimize various...
  • DeepTrack

  • Referenced in 2 articles [sw27576]
  • loss function that maintains as many training samples as possible and reduces the risk ... ordinary Stochastic Gradient Descent approach in CNN training with a robust sample selection mechanism...
  • ZhuSuan

  • Referenced in 2 articles [sw27939]
  • objectives and advanced gradient estimators (SGVB, REINFORCE, VIMCO, etc.). Importance sampling for learning and evaluating...
  • COMBIgor

  • Referenced in 1 article [sw28386]
  • experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization...
  • IPSep-CoLa

  • Referenced in 8 articles [sw09789]
  • give an incremental algorithm based on gradient projection for efficiently solving this problem. The algorithm ... demonstrate the utility of our technique with sample data from a number of practical applications...
  • MINMOD

  • Referenced in 10 articles [sw16356]
  • factors, using computer analysis of a frequently-sampled intravenous glucose tolerance test (FSIGT). This ‘minimal ... squares estimation technique is used, employing a gradient-type of estimation algorithm, and the first...
  • ZOOjl

  • Referenced in 1 article [sw22397]
  • gradient of the objective function, but instead, learns from samples of the search space...
  • QUIC

  • Referenced in 5 articles [sw11795]
  • Gaussian Markov Random Field, from very limited samples. We propose a novel algorithm for solving ... methods that largely use first order gradient information, our algorithm is based on Newton...
  • ASTRO-DF

  • Referenced in 3 articles [sw26833]
  • ASTRO-DF: a class of adaptive sampling trust-region algorithms for derivative-free stochastic optimization ... provide no direct observations of the function gradient. We present ASTRO-DF -- a class ... sense that the extent of Monte Carlo sampling is determined by continuously monitoring and balancing...
  • sparseHessianFD

  • Referenced in 2 articles [sw23054]
  • improve efficiency of numerical optimization and sampling algorithms. By exploiting the known sparsity pattern ... sparseHessianFD package require many fewer function or gradient evaluations than would be required...