Y. Yuan

1.9k total citations · 1 hit paper
7 papers, 1.4k citations indexed

About

Y. Yuan is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Y. Yuan has authored 7 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Numerical Analysis, 4 papers in Computational Theory and Mathematics and 2 papers in Computational Mechanics. Recurrent topics in Y. Yuan's work include Advanced Optimization Algorithms Research (6 papers), Iterative Methods for Nonlinear Equations (3 papers) and Optimization and Variational Analysis (2 papers). Y. Yuan is often cited by papers focused on Advanced Optimization Algorithms Research (6 papers), Iterative Methods for Nonlinear Equations (3 papers) and Optimization and Variational Analysis (2 papers). Y. Yuan collaborates with scholars based in United Kingdom. Y. Yuan's co-authors include Y. H. Dai and M. J. D. Powell and has published in prestigious journals such as Mathematical Programming, SIAM Journal on Optimization and IMA Journal of Numerical Analysis.

In The Last Decade

Y. Yuan

7 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property

1999 960 citations Y. H. Dai, Y. Yuan SIAM Journal on Optimization profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Y. Yuan United Kingdom	7	1.0k	645	557	168	147	7	1.4k
Wenyu Sun China	14	870 0.8×	669 1.0×	422 0.8×	197 1.2×	212 1.4×	69	1.4k
A. Miele United States	28	607 0.6×	479 0.7×	465 0.8×	392 2.3×	56 0.4×	148	2.5k
A. A. Goldstein United States	14	940 0.9×	954 1.5×	459 0.8×	237 1.4×	221 1.5×	35	1.8k
Robert S. Womersley Australia	23	715 0.7×	614 1.0×	415 0.7×	117 0.7×	103 0.7×	53	1.4k
Neculai Andrei Romania	26	1.5k 1.4×	881 1.4×	688 1.2×	170 1.0×	211 1.4×	48	1.8k
Sandra A. Santos Brazil	20	782 0.8×	703 1.1×	431 0.8×	138 0.8×	188 1.3×	68	1.2k
Luigi Grippo Italy	19	1.7k 1.6×	1.3k 2.0×	627 1.1×	393 2.3×	429 2.9×	42	2.3k
Aris Daniilidis France	18	665 0.6×	972 1.5×	598 1.1×	146 0.9×	158 1.1×	51	1.6k
George G. Lorentz United States	7	854 0.8×	226 0.4×	421 0.8×	89 0.5×	190 1.3×	10	2.1k
Y. H. Dai China	12	1.7k 1.6×	968 1.5×	949 1.7×	143 0.9×	214 1.5×	17	2.2k

Countries citing papers authored by Y. Yuan

Since Specialization

Citations

This map shows the geographic impact of Y. Yuan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Y. Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Y. Yuan more than expected).

Fields of papers citing papers by Y. Yuan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Y. Yuan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Y. Yuan. The network helps show where Y. Yuan may publish in the future.

Co-authorship network of co-authors of Y. Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Y. Yuan. A scholar is included among the top collaborators of Y. Yuan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Y. Yuan. Y. Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Dai, Y. H. & Y. Yuan. (1999). A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property. SIAM Journal on Optimization. 10(1). 177–182. 960 indexed citations breakdown →

2.

Yuan, Y.. (1990). On a subproblem of trust region algorithms for constrained optimization. Mathematical Programming. 47(1-3). 53–63. 103 indexed citations

3.

Powell, M. J. D. & Y. Yuan. (1990). A trust region algorithm for equality constrained optimization. Mathematical Programming. 49(1-3). 189–211. 156 indexed citations

4.

Powell, M. J. D. & Y. Yuan. (1986). A recursive quadratic programming algorithm that uses differentiable exact penalty functions. Mathematical Programming. 35(3). 265–278. 76 indexed citations

5.

Yuan, Y.. (1985). On the superlinear convergence of a trust region algorithm for nonsmooth optimization. Mathematical Programming. 31(3). 269–285. 50 indexed citations

6.

Yuan, Y.. (1984). An Example of Only Linear Convergence of Trust Region Algorithms for Non-smooth Optimization. IMA Journal of Numerical Analysis. 4(3). 327–335. 20 indexed citations

7.

Powell, M. J. D. & Y. Yuan. (1984). Conditions for Superlinear Convergence in l1 and l Solutions of Overdetermined Non-linear Equations. IMA Journal of Numerical Analysis. 4(2). 241–251. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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