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D-Index & Metrics

Mathematics

D-Index
53
Citations
27237
World Ranking
869
National Ranking
417

Engineering and Technology

D-Index
53
Citations
27289
World Ranking
3299
National Ranking
968

Research.com Recognitions

  • 2020 - SIAM Fellow For fundamental contributions to the theory and algorithms for nonlinear optimization.

Overview

Richard H. Byrd is affiliated with the University of Colorado Boulder in the United States. Their research primarily addresses topics within Mathematics and Computer Science, encompassing both main and subfields related to numerical and computational methods.

The main fields of study covered in their work include:

  • Mathematics
  • Computer Science

Within subfields of study, their research focuses on:

  • Numerical Analysis
  • Computational Theory and Mathematics

The topics frequently explored in their publications are:

  • Advanced Optimization Algorithms Research
  • Iterative Methods for Nonlinear Equations
  • Optimization and Variational Analysis

One recent paper authored in collaboration with Yuchen Xie is titled "Analysis of the BFGS Method with Errors", published in 2020 in the SIAM Journal on Optimization. This work has been cited 29 times. The SIAM Journal on Optimization also represents a frequent publication venue for their research.

Their coauthors include:

  • Yuchen Xie
  • Jorge Nocedal

Richard H. Byrd's contributions have been recognized with the award of SIAM Fellow in 2020 for fundamental contributions to the theory and algorithms for nonlinear optimization.

Best Publications

  • A limited memory algorithm for bound constrained optimization

    Richard H. Byrd;Peihuang Lu;Jorge Nocedal;Ciyou Zhu

  • Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization

    Ciyou Zhu;Richard H. Byrd;Peihuang Lu;Jorge Nocedal

  • An Interior Point Algorithm for Large-Scale Nonlinear Programming

    Richard H. Byrd;Mary E. Hribar;Jorge Nocedal

  • A trust region method based on interior point techniques for nonlinear programming

    Richard H. Byrd;Jean Charles Gilbert;Jorge Nocedal

  • Knitro: An Integrated Package for Nonlinear Optimization

    Richard H. Byrd;Jorge Nocedal;Richard A. Waltz

  • Representations of quasi-Newton matrices and their use in limited memory methods

    Richard H. Byrd;Jorge Nocedal;Robert B. Schnabel

  • Approximate solution of the trust region problem by minimization over two-dimensional subspaces

    Richard H. Byrd;Robert B. Schnabel;Gerald A. Shultz

  • A Stochastic Quasi-Newton Method for Large-Scale Optimization

    Richard H. Byrd;S. L. Hansen;Jorge Nocedal;Yoram Singer

  • A tool for the analysis of Quasi-Newton methods with application to unconstrained minimization

    Richard H. Byrd;Jorge Nocedal

  • A Trust Region Algorithm for Nonlinearly Constrained Optimization

    Richard H. Byrd;Robert B. Schnabel;Gerald A. Shultz

  • A Stable and Efficient Algorithm for Nonlinear Orthogonal Distance Regression

    Paul T. Boggs;Richard H. Byrd;Robert B. Schnabel

  • Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems

    Richard H. Byrd;Jorge Nocedal;Ya-Xiang Yuan

  • Sample size selection in optimization methods for machine learning

    Richard H. Byrd;Gillian M. Chin;Jorge Nocedal;Yuchen Wu

  • A Family of Trust Region Based Algorithms for Unconstrained Minimization with Strong Global Convergence Properties.

    Gerald A. Shultz;Robert B. Schnabel;Richard H. Byrd

  • Algorithm 676: ODRPACK: software for weighted orthogonal distance regression

    Paul T. Boggs;Janet R. Donaldson;Richaard h. Byrd;Robert B. Schnabel

  • ON THE USE OF STOCHASTIC HESSIAN INFORMATION IN OPTIMIZATION METHODS FOR MACHINE LEARNING

    Richard H. Byrd;Gillian M. Chin;Will Neveitt;Jorge Nocedal

  • User's reference guide for ODRPACK version 2.01:: software for weighted orthogonal distance regression

    Paul T Boggs;Richard H Byrd;Janet E Rogers;Robert B Schnabel

  • An algorithm for nonlinear optimization using linear programming and equality constrained subproblems

    Richard H. Byrd;Nicholas I. M. Gould;Jorge Nocedal;Richard A. Waltz

  • Exact and inexact subsampled Newton methods for optimization

    Raghu Bollapragada;Richard H. Byrd;Jorge Nocedal

  • A limited-memory algorithm for bound-constrained optimization

    R.H. Byrd;L. Peihuang;J. Nocedal

  • A Family of Trust Region Based Algorithms for Unconstrained Minimization with Strong Global Convergence Properties ; CU-CS-216-82

    Gerald A Shultz;Robert B Schnabel;Richard H Byrd

  • A Trust Region Algorithm for Nonlinearly Constrained Optimization ; CU-CS-313-85

    Richard H Byrd;Robert B Schnabel;Gerald A Shultz

  • Approximate Solution of the Trust Region Problem by Minimization over Two-Dimensional Subspaces ; CU-CS-346-86

    Richard H Byrd;Robert B Schnabel;Gerald A Schultz

Frequent Co-Authors

Robert B. Schnabel
Robert B. Schnabel University of Colorado Boulder
Jorge Nocedal
Jorge Nocedal Northwestern University
Teresa Head-Gordon
Teresa Head-Gordon University of California, Berkeley
Nicholas I. M. Gould
Nicholas I. M. Gould University of Oxford
André van der Hoek
André van der Hoek University of California, Irvine
Tim Curran
Tim Curran University of Colorado Boulder
Xiao-Chuan Cai
Xiao-Chuan Cai University of Colorado Boulder
Yin Zhang
Yin Zhang Chinese University of Hong Kong, Shenzhen
Ya-xiang Yuan
Ya-xiang Yuan Chinese Academy of Sciences

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