• MSS

  • Referenced in 6 articles [sw08530]
  • method computes the minimizer of a quadratic function defined by a limited-memory BFGS matrix ... adaptation of the Moré-Sorensen direct method into an L-BFGS setting for large-scale...
  • OptimPack

  • Referenced in 1 article [sw26295]
  • VMLM-B: a variable metric method with limited memory requirements and, possibly, bound constraints ... parameters. The algorithm is based on limited memory BFGS updates [1] with Moré & Thuente inexact ... gradient projection to account for bounds. The method has been described in [3]. In order...
  • PENSDP

  • Referenced in 24 articles [sw05119]
  • using iterative solvers The limiting factors of second-order methods for large-scale semidefinite optimization ... particular algorithm based on the modified barrier method, we propose to use iterative solvers instead ... direct factorization techniques. The preconditioned conjugate gradient method proves to be a viable alternative ... formula. This leads to huge savings in memory requirements and, for certain problems, to further...
  • libLBFGS

  • Referenced in 3 articles [sw33308]
  • implementation of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method written by Jorge Nocedal...
  • Evolino

  • Referenced in 19 articles [sw36450]
  • learning. Current Neural Network learning algorithms are limited in their ability to model non-linear ... good RNN hidden node weights, while using methods such as linear regression or quadratic programming ... output. Using the Long Short-Term Memory RNN Architecture, the method is tested in three...
  • DOST

  • Referenced in 9 articles [sw13155]
  • orthonormal Stockwell transform. We present an efficient method for computing the discrete orthonormal Stockwell transform ... great promise in various applications, but is limited because its computation is infeasible for most ... solving many of the memory and computational issues. However, computing the DOST of a signal ... computational complexity of our method is 𝒪(NlogN), putting it in the same category...
  • AutoKeras

  • Referenced in 7 articles [sw33648]
  • open-source AutoML system based on our method, namely Auto-Keras. The system runs ... adaptive search strategy for different GPU memory limits...
  • BLITZ

  • Referenced in 6 articles [sw37121]
  • progress toward convergence. This result motivates methods for optimizing algorithmic parameters and discarding irrelevant variables ... convincingly outperforms existing solvers in sequential, limited-memory, and distributed settings. BLITZ is not specific...
  • ALBERT

  • Referenced in 10 articles [sw36207]
  • increases become harder due to GPU/TPU memory limitations and longer training times. To address these ... present two parameter-reduction techniques to lower memory consumption and increase the training speed ... Comprehensive empirical evidence shows that our proposed methods lead to models that scale much better...
  • HSL_MA77

  • Referenced in 15 articles [sw13924]
  • core sparse Cholesky solver. Direct methods for solving large sparse linear systems of equations ... robustness. Their main weakness is that the memory they require usually increases rapidly with problem ... direct solver that aims to circumvent this limitation by allowing the system matrix, intermediate data...
  • ADDA

  • Referenced in 4 articles [sw30342]
  • dipole-approximation code ADDA: Capabilities and known limitations. The open-source code ADDA is described ... implements the discrete dipole approximation (DDA), a method to simulate light scattering by finite ... ADDA can run on a multiprocessor distributed-memory system, parallelizing a single DDA calculation. Hence ... scatterer is in principle limited only by total available memory and computational speed. ADDA...
  • PREQN

  • Referenced in 9 articles [sw01233]
  • automatically generating preconditioners for the conjugate gradient method. It is designed for solving a sequence ... optimization. The preconditioners are based on limited-memory quasi-Newton updating and are recommended...
  • Sarment

  • Referenced in 2 articles [sw29814]
  • methods or maximal partitioning. Data storage and heavy computation are written in C++, to limit ... memory use and time consumption. Then, compilation process is needed to install Sarment...
  • sldg

  • Referenced in 8 articles [sw17637]
  • conservative, local in space, and able to limit numerical diffusion, they are considered a promising ... semi-Lagrangian discontinuous Galerkin method for distributed memory systems (so-called clusters). Both strong...
  • gridfit

  • Referenced in 6 articles [sw22539]
  • smoothing done, as well as interpolation methods, which solver to use, etc. This release allows ... tiling option. There is essentially no limit on the size of the suface one builds ... have dense enough data and enough memory to store the final gridded surface...
  • CBCM

  • Referenced in 1 article [sw02331]
  • high-dimensional data. However, most clustering methods for the data miming applications do not work ... limitation of available memory. In this paper, we propose a new cell-based clustering method...
  • gridlod

  • Referenced in 4 articles [sw34719]
  • used in the localized orthogonal decomposition (LOD) method for numerical homogenization. The code works ... also greater than 3) but is limited to computations on the hypercube ... code is written with consideration of the memory usage. Thus, the Petrov--Galerkin formulation...
  • OPALQP

  • Referenced in 8 articles [sw04847]
  • Fortran subroutine implementing a sequential quadratic programming method for nonlinearly constrained optimization. It was originally ... constraint normals, the use of limited memory updates for approximating the Hessian of the Lagrangian...
  • crowdGPPL

  • Referenced in 1 article [sw34403]
  • arising from noisy and sparse data. Our method exploits input features, such as text embeddings ... limits computational and memory costs. Our experiments on a recommendation task show that our method...
  • k-Neighborhood

  • Referenced in 3 articles [sw13966]
  • agents with imperfect recall. Solving a (limited memory) influence diagram is an NP-hard problem ... local search; experiments show that our methods improve on current local search algorithms both with...