World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
10993
World Ranking
7439
National Ranking
980

Mathematics

D-Index
45
Citations
11163
World Ranking
1439
National Ranking
76

Research.com Recognitions

  • 2013 - Fellow of the American Mathematical Society
  • 2011 - SIAM Fellow For contributions to nonlinear optimization and leadership of computational mathematics in China.

Overview

Ya-xiang Yuan is affiliated with the Chinese Academy of Sciences in China. Their research spans multiple fields including Mathematics, Computer Science, and Engineering, with a significant body of work comprising 44 publications each in Mathematics and Computer Science, and 31 in Engineering.

Their main subfields of study include Numerical Analysis, Computational Mechanics, Computational Theory and Mathematics, Artificial Intelligence, and Computational Mathematics.

Ya-xiang Yuan's research topics encompass advanced optimization algorithms, sparse and compressive sensing techniques, matrix theory and algorithms, stochastic gradient optimization techniques, tensor decomposition and applications, numerical methods in inverse problems, and optimization and variational analysis.

The scientist has published in several venues, with frequent appearances in the following journals and repositories:

  • arXiv (Cornell University)
  • Journal of the Operations Research Society of China
  • Computational Optimization and Applications
  • SIAM Journal on Optimization
  • IMA Journal of Numerical Analysis

Notable papers authored or co-authored by Ya-xiang Yuan include:

  • "A Brief Introduction to Manifold Optimization," 2020, Journal of the Operations Research Society of China
  • "On the complexity of an augmented Lagrangian method for nonconvex optimization," 2020, IMA Journal of Numerical Analysis
  • "A class of smooth exact penalty function methods for optimization problems with orthogonality constraints," 2020, Optimization Methods & Software
  • "Homogenization for polynomial optimization with unbounded sets," 2022, Mathematical Programming
  • "Exact Penalty Function for ℓ₂,₁ Norm Minimization over the Stiefel Manifold," 2021, SIAM Journal on Optimization

Frequent collaborators of Ya-xiang Yuan include:

  • Renfeng Peng
  • Bin Gao
  • Zaiwen Wen
  • Jiawang Nie
  • Xin Liu

Ya-xiang Yuan has received recognition in the form of prestigious awards such as being named a Fellow of the American Mathematical Society in 2013 and a SIAM Fellow in 2011 for contributions to nonlinear optimization and leadership of computational mathematics in China.

Best Publications

  • A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property

    Y. H. Dai;Y. Yuan

  • Optimization Theory and Methods: Nonlinear Programming

    Wenyu Sun;Ya-Xiang Yuan

  • Optimization theory and methods

    Wenyu Sun;Ya-Xiang Yuan

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

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

  • An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimization

    Y. H. Dai;Ya-Xiang Yuan

  • A trust region algorithm for equality constrained optimization

    M. J. D. Powell;Y. Yuan

  • On the quadratic convergence of the Levenberg-Marquardt method without nonsingularity assumption

    Jin-yan Fan;Ya-xiang Yuan

  • Combining Trust Region and Line Search Techniques

    Jorge Nocedal;Ya-xiang Yuan

  • Convergence Properties of Nonlinear Conjugate Gradient Methods

    Yuhong Dai;Jiye Han;Guanghui Liu;Defeng Sun

  • Recent advances in trust region algorithms

    Ya-Xiang Yuan

  • A modified BFGS algorithm for unconstrained optimization

    Ya-Xiang Yuan

  • Convergence properties of the Fletcher-Reeves method

    Y. H. Dai;Y. Yuan

  • On a subproblem of trust region algorithms for constrained optimization

    Ya-Xiang Yuan

  • A Brief Introduction to Manifold Optimization

    Jiang Hu;Xin Liu;Zai-Wen Wen;Ya-Xiang Yuan

  • A recursive quadratic programming algorithm that uses differentiable exact penalty functions

    M J D Powell;Y Yuan

  • Conditions for convergence of trust region algorithms for nonsmooth optimization

    Ya-Xiang Yuan

  • On the convergence of a new trust region algorithm

    Ya-xiang Yuan

  • Modified Two-Point Stepsize Gradient Methods for Unconstrained Optimization

    Yuhong Dai;Jinyun Yuan;Ya-Xiang Yuan

  • Alternate minimization gradient method

    Yu‐Hong Dai;Ya‐Xiang Yuan

  • Optimality Conditions for the Minimization of a Quadratic with Two Quadratic Constraints

    Ji-Ming Peng;Ya-xiang Yuan

Frequent Co-Authors

Yu-Hong Dai
Yu-Hong Dai Chinese Academy of Sciences
M. J. D. Powell
M. J. D. Powell University of Cambridge
Philippe L. Toint
Philippe L. Toint University of Namur
Jorge Nocedal
Jorge Nocedal Northwestern University
Shiqian Ma
Shiqian Ma Rice University
Andreas Griewank
Andreas Griewank Humboldt-Universität zu Berlin
Andrzej Ruszczyński
Andrzej Ruszczyński Rutgers, The State University of New Jersey
Henry Wolkowicz
Henry Wolkowicz University of Waterloo
Luís Nunes Vicente
Luís Nunes Vicente Lehigh University
Masao Fukushima
Masao Fukushima Kyoto University

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