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Block truncated-Newton methods for parallel optimization
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Solution of nonlinear least squares problems on a multiprocessor
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A discrete Newton algorithm for minimizing a function of many variables
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Newton-type methods for unconstrained and linearly constrained optimization
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Parallel quasi-Newton methods for unconstrained optimization
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Using parallel function evaluations to improve hessian approximation for unconstrained optimization
inferredcites →https://doi.org/10.1007/bf02592055openalex-snapshot
Truncated-Newton algorithms for large-scale unconstrained optimization
inferredcites →https://doi.org/10.1016/0024-3795(80)90247-5openalex-snapshot
The block conjugate gradient algorithm and related methods
inferredcites →https://doi.org/10.1016/0167-6377(90)90065-dopenalex-snapshot
Assessing a search direction within a truncated-newton method
inferredcites →https://doi.org/10.1016/0167-8191(87)90013-5openalex-snapshot
Parallel implementation of the block conjugate gradient algorithm
inferredcites →https://doi.org/10.1016/b978-0-12-141050-6.50023-4openalex-snapshot
A GENERALIZED CONJUGATE GRADIENT METHOD FOR THE NUMERICAL SOLUTION OF ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS
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Computer Science and Statistics: Proceedings of the 17th Symposium on the Interface
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Solution of Sparse Indefinite Systems of Linear Equations
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Newton-Type Minimization via the Lanczos Method
inferredcites →https://doi.org/10.1137/0906042openalex-snapshot
Preconditioning of Truncated-Newton Methods
inferredcites →https://doi.org/10.1137/1.9781611971774openalex-snapshot
Solution of Partial Differential Equations on Vector and Parallel Computers
inferredcites →https://doi.org/10.1137/1027055openalex-snapshot
Solution of Partial Differential Equations on Vector and Parallel Computers
inferredcites →https://doi.org/10.1287/opre.34.5.667openalex-snapshot
Nonlinear Network Programming on Vector Supercomputers: A Study on the CRAY X-MP
inferredcites →https://doi.org/10.21236/ada193250openalex-snapshot
Parallel Quasi-Newton Methods for Unconstrained Optimization.
inferredcites →https://doi.org/10.6028/jres.049.044openalex-snapshot
Methods of conjugate gradients for solving linear systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Some Perspectives on High-Performance Mathematical Software
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Data Assimilation for Numerical Weather Prediction: A Review
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Parallel Nonlinear Optimization: Limitations, Challenges, and Opportunities
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A truncated Newton optimization algorithm in meteorology applications with analytic Hessian/vector products
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A view of the limitations, opportunities, and challenges in parallel nonlinear optimization
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Parallel low-memory quasi-Newton optimization algorithm for molecular structure
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Explicit and implicit viscoplastic models for polymeric composite
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Truncated-Newton training algorithm for neurocomputational viscoplastic model
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Newton's Method in Shape Optimisation: A Three-Dimensional Case
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Quasi-Newton parallel geometry optimization methods
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An alternative globalization strategy for unconstrained optimization
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An exact penalty-lagrangian approach for a class of constrained optimization problems with bounded variables
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A curvilinear search algorithm for unconstrained optimization by automatic differentiation
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Parallel interior-point solver for block-structured nonlinear programs on SIMD/GPU architectures
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A parallel tensor algorithm for nonlinear optimization
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Interior-point methodology for 3-D PET reconstruction
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A data-parallel algorithm for iterative tomographic image reconstruction
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A Numerical Study of the Limited Memory BFGS Method and the Truncated-Newton Method for Large Scale Optimization
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Direct Search Methods on Parallel Machines
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A General-Purpose Parallel Algorithm for Unconstrained Optimization
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Parallel Block-Partitioning of Truncated Newton for Nonlinear Network Optimization
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A Primal-Dual Method for Large-Scale Image Reconstruction in Emission Tomography
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Algorithm 711: BTN: software for parallel unconstrained optimization
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Convergence analysis of a parallel newton scheme for dynamic power grid simulations
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Application of a New Adjoint Newton Algorithm to the 3D ARPS Storm-Scale Model Using Simulated Data
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Second-Order Information in Data Assimilation*
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Parallel Distributed Optimization Method based on Resource Addition and Reduction.
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Smart distributed minimization of the volume of discrete structures
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A Reliable Effective Terascale Linear Learning System
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