• KELLEY

  • Referenced in 621 articles [sw04829]
  • part, occupying approximately 100 pages, is devoted to the optimization of smooth functions. The methods ... also second order derivatives of the objective function. The first part contains five chapters ... which is approximately 50 pages long, deals with the optimization of noisy functions. Such optimization ... approximations of the gradient, which are adjusted to the noise level in the function. Direct...
  • OPQ

  • Referenced in 405 articles [sw11881]
  • Computation and approximation. Orthogonal polynomials are a widely used class of mathematical functions that...
  • CompEcon

  • Referenced in 49 articles [sw04789]
  • integrated set of routines for function approximation using polynomial, splines and other functional families...
  • TANE

  • Referenced in 39 articles [sw02196]
  • TANE: An efficient algorithm for discovering functional and approximate dependencies. environments. The discovery of functional ... values, which makes testing the validity of functional dependencies fast even for a large number ... partitions also makes the discovery of approximate functional dependencies easy and efficient and the erroneous...
  • CMA-ES

  • Referenced in 111 articles [sw05063]
  • model of the underlying objective function similar to the approximation of the inverse Hessian matrix ... nature of the underlying objective function are made. Only the ranking between candidate solutions...
  • EGO

  • Referenced in 366 articles [sw07588]
  • data collected by evaluating the objective function at a few points. Then, EGO balances between ... minimum of the surface and improving the approximation by sampling where the prediction error...
  • UOBYQA

  • Referenced in 64 articles [sw07576]
  • UOBYQA: unconstrained optimization by quadratic approximation. A new algorithm for general unconstrained optimization calculations ... account of the curvature of the objective function by forming quadratic models by interpolation. Obviously ... interpolation point is moved. The Lagrange functions assist the procedure that improves the model ... error of the quadratic approximation of the function being minimized. It is pointed out that...
  • AutoClass

  • Referenced in 68 articles [sw26092]
  • classifications with an approximate posterior probability of the distribution function w.r.t. the data, obtained ... marginalizing over all the parameters. Approximation is necessitated by the computational complexity of the joint ... rating allows direct comparison of alternate density functions that differ in number of classes and/or ... individual class density functions. We discuss the rationale behind our approach to classification. We give...
  • Sinc-Pack

  • Referenced in 73 articles [sw13600]
  • This book deals with the approximation by sinc functions and the application to the numerical...
  • Approxrl

  • Referenced in 31 articles [sw14312]
  • contains Matlab implementations of a number of approximate reinforcement learning (RL) and dynamic programming ... Reinforcement Learning and Dynamic Programming Using Function Approximators, CRC Press, Automation and Control Engineering Series...
  • SNOPT

  • Referenced in 528 articles [sw02300]
  • that uses a smooth augmented Lagrangian merit function and makes explicit provision for infeasibility ... based on a limited-memory quasi-Newton approximation to the Hessian of the Lagrangian...
  • GAMESS

  • Referenced in 39 articles [sw03002]
  • approaches, as well as the Density Functional Theory approximation. Excited states can be computed...
  • CONLIN

  • Referenced in 47 articles [sw14151]
  • first order, conservative approximations to the objective function and to the constraints. The primary optimization ... therefore replaced with a sequence of explicit approximate problems having a simple algebraic structure ... CONLIN strategy. The maximum of the dual function is sought in a sequence of dual ... itself replaced with a sequence of approximate quadratic subproblems with non-negativity constraints...
  • Chebfun2

  • Referenced in 38 articles [sw12708]
  • rank approximants), where u(y) and v(x) are univariate functions which in turn ... Chebfun objects. The so-called low rank approximations are constructed using an iterative algorithm that ... functions of two variables is of low rank or can be approximated...
  • MLMSRBF

  • Referenced in 41 articles [sw07571]
  • global optimization of computationally expensive multimodal functions when derivatives are unavailable. The proposed Stochastic Response ... response surface model to approximate the expensive function and identifies a promising point for function...
  • HSL-VF05

  • Referenced in 68 articles [sw36311]
  • Lanczos method. The approximate minimization of a quadratic function within an ellipsoidal trust region...
  • ApproxFun

  • Referenced in 14 articles [sw22772]
  • ApproxFun.jl: Julia package for function approximation . ApproxFun is a package for approximating functions...
  • Spinterp

  • Referenced in 40 articles [sw00902]
  • recover or approximate smooth multivariate functions, sparse grids are superior to full grids...
  • DGM

  • Referenced in 63 articles [sw39282]
  • basis functions. In addition, we prove a theorem regarding the approximation power of neural networks...
  • PROC NLMIXED

  • Referenced in 65 articles [sw11039]
  • their approximate standard errors based on the second derivative matrix of the likelihood function. PROC ... estimate arbitrary functions of the nonrandom parameters, and PROC NLMIXED computes their approximate standard errors...