• GradSamp

  • Referenced in 118 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 62 articles [sw05188]
  • based on quasi-Newton updating and gradient sampling...
  • HANSO

  • Referenced in 18 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 77 articles [sw05202]
  • optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion...
  • SLQP-GS

  • Referenced in 9 articles [sw05162]
  • Sequential Linear or Quadratic Programming with Gradient Sampling (Matlab...
  • Wirtinger Flow

  • Referenced in 110 articles [sw34175]
  • knowledge of the phase of these samples would yield a linear system). This paper develops ... computational complexity, much like in a gradient descent scheme. The main contribution is that this...
  • IMFIL

  • Referenced in 44 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...
  • QUIC

  • Referenced in 34 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...
  • CONMIN

  • Referenced in 51 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...
  • GPDT

  • Referenced in 46 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...
  • Finito

  • Referenced in 18 articles [sw38276]
  • Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems. Recent advances in optimization ... This method is also amendable to a sampling without replacement scheme that in practice gives...
  • GRAMPC

  • Referenced in 7 articles [sw30732]
  • embedded nonlinear model predictive control using a gradient-based augmented Lagrangian approach (GRAMPC). A nonlinear ... that is suitable for dynamical systems with sampling times in the (sub)millisecond range ... augmented Lagrangian formulation with a tailored gradient method for the inner minimization problem. The algorithm...
  • ABCRATE

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

  • Referenced in 2 articles [sw41466]
  • gradient Langevin dynamics (SGLD) algorithm has achieved great success in Bayesian learning and posterior sampling ... large variance caused by the stochastic gradient. In order to alleviate these drawbacks, we leverage ... smoothing stochastic gradient Langevin dynamics (LS-SGLD) algorithm. We prove that for sampling from both...
  • NESVM

  • Referenced in 6 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...
  • ASTRO-DF

  • Referenced in 12 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...
  • 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...
  • BoTorch

  • Referenced in 6 articles [sw40383]
  • Monte-Carlo (MC) acquisition functions, a novel sample average approximation optimization approach, auto-differentiation ... novel ”one-shot” formulation of the Knowledge Gradient, enabled by a combination of our theoretical ... contributions. In experiments, we demonstrate the improved sample efficiency of BoTorch relative to other popular...
  • 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...
  • DiSCO

  • Referenced in 12 articles [sw28439]
  • computed by a distributed preconditioned conjugate gradient method. We analyze its iteration complexity and communication ... where the n data points are i.i.d. sampled and when the regularization parameter scales...