Frank E. Curtis

2.1k citations
63 papers · 1.0k indexed · h-index 20
Topics
Advanced Optimization Algorithms Research (47 papers)Sparse and Compressive Sensing Techniques (34 papers)Stochastic Gradient Optimization Techniques (18 papers)

In The Last Decade

Frank E. Curtis

58 papers receiving 927 citations

Peers

Frank E. Curtis
Comparison fields: 5 of 105
  • Numerical Analysis 532
  • Computational Theory and Mathematics 397
  • Computational Mechanics 374
  • Artificial Intelligence 271
  • Control and Systems Engineering 225
Replace Ion Necoara with:
Ion Necoara Romania
Yu. E. Nesterov Belgium
Guoqiang Wang China
Francesco Rinaldi Italy
Levent Tunçel Canada
Napsu Karmitsa Finland
Clóvis C. Gonzaga Brazil
Jiming Peng United States
Houduo Qi United Kingdom
Zhiyou Wu China
Frank E. Curtis relative to Ion Necoara Romania Ion Necoara's profile →
Citations per field
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Countries citing papers authored by Frank E. Curtis

Since Specialization
Citations

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

Fields of papers citing papers by Frank E. Curtis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank E. Curtis. 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 Frank E. Curtis. The network helps show where Frank E. Curtis may publish in the future.

Co-authorship network of co-authors of Frank E. Curtis

This figure shows the co-authorship network connecting the top 25 collaborators of Frank E. Curtis. A scholar is included among the top collaborators of Frank E. Curtis 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 Frank E. Curtis. Frank E. Curtis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 4
3 0
4 2
5 3
6 16
7 1
8 21
9 2
10 8
11 18
12 25
13 11
14 11
15
A self-correcting variable-metric algorithm for stochastic optimization
8
16 23
17 2
18 38
19 5
20 4

About Frank E. Curtis

Frank E. Curtis is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics, having authored 63 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (47 papers), Sparse and Compressive Sensing Techniques (34 papers) and Stochastic Gradient Optimization Techniques (18 papers). The work is most often cited by research in Numerical Analysis (532 citations), Computational Theory and Mathematics (397 citations) and Computational Mechanics (374 citations). Frank E. Curtis has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Daniel P. Robinson, Jorge Nocedal, Michael L. Overton, Richard H. Byrd, Andreas Wächter, Katya Scheinberg, Olaf Schenk, Rui Shi, Hao Jiang and Zheng Han. Their work appears in journals such as Chemistry of Materials, Operations Research and IEEE Signal Processing Magazine.

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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