Jay S. Treiman

558 citations
21 papers · 336 · h-index 11

Impact in

Papers in

Jay S. Treiman

20 papers receiving 294 citations

Peers

Jay S. Treiman
Comparison fields: 5 of 33
  • Numerical Analysis 161
  • Computational Theory and Mathematics 290
  • Geometry and Topology 75
  • Applied Mathematics 89
  • Mathematical Physics 68
Replace A. A. Milyutin with:
A. A. Milyutin
Jean-Baptiste Hiriart-Urruty France
József J. Kolumbán Romania
Hadi Khatibzadeh Iran
B.Sh. Mordukhovich Russia
Jean-Noël Corvellec France
Espedito De Pascale Italy
L. R. Lucambio Pérez Brazil
Ivan Ginchev Italy
J. P. Revalski Bulgaria
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Citations per field
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A. A. Milyutin · 1×
Citations per year

Countries citing papers authored by Jay S. Treiman

Since Specialization
Citations

This map shows the geographic impact of Jay S. Treiman'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 Jay S. Treiman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay S. Treiman more than expected).

Fields of papers citing papers by Jay S. Treiman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay S. Treiman. 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 Jay S. Treiman. The network helps show where Jay S. Treiman may publish in the future.

Co-authors

The 5 scholars most cited alongside Jay S. Treiman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jay S. Treiman Line = papers co-authored together Jay S. Treiman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200351
2 199545
3 198832
4 199831
5 198331
6 198628
7 199925
8 200017
9 199515
10 198510
11 198910
12 19999
13 20128
14 19867
15
A new characterization of Clarke's tangent cone and its applications to subgradient analysis and optimization
19835
16
Helly's Intersection Theorem on Manifolds of Nonpositive Curvature
20064
17 19914
18 19902
19 20141
20 20021

About Jay S. Treiman

Jay S. Treiman is a scholar working on Computational Theory and Mathematics, Numerical Analysis, Applied Mathematics, Mathematical Physics and Computational Mechanics, having authored 21 papers that have together received 336 indexed citations. Recurring topics across this work include Optimization and Variational Analysis (14 papers), Advanced Optimization Algorithms Research (9 papers), Nonlinear Partial Differential Equations (5 papers), Numerical methods in inverse problems (4 papers), Advanced Banach Space Theory (4 papers), Point processes and geometric inequalities (2 papers), Advanced Mathematical Modeling in Engineering (2 papers) and Geometric Analysis and Curvature Flows (2 papers). The work is most often cited by research in Numerical Analysis (161 citations), Computational Theory and Mathematics (290 citations), Geometry and Topology (75 citations), Applied Mathematics (89 citations) and Mathematical Physics (68 citations). Jay S. Treiman has collaborated with scholars based in United States, Canada and Russia. Frequent co-authors include Qiji Jim Zhu, Boris S. Mordukhovich, Jonathan M. Borwein, A. H. Treiman and Yuri S. Ledyaev. Their work appears in journals such as Nonlinear Analysis, Transactions of the American Mathematical Society, SIAM Journal on Optimization, Journal of Optimization Theory and Applications and SIAM Journal on Control and Optimization.

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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