Aaron Sidford

2.2k citations
37 papers · 546 · h-index 12

Impact in

Papers in

Aaron Sidford

34 papers receiving 513 citations

Peers

Aaron Sidford
Comparison fields: 5 of 62
  • Computational Theory and Mathematics 318
  • Numerical Analysis 93
  • Computational Mathematics 10
  • Computer Graphics and Computer-Aided Design 41
  • Statistics and Probability 75
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Citations per field
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Citations per year

Countries citing papers authored by Aaron Sidford

Since Specialization
Citations

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

Fields of papers citing papers by Aaron Sidford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aaron Sidford. 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 Aaron Sidford. The network helps show where Aaron Sidford may publish in the future.

Co-authors

The 25 scholars most cited alongside Aaron Sidford, 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 Aaron Sidford Line = papers co-authored together Aaron Sidford links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201886
2 201479
3 201366
4 201547
5 202030
6 202025
7 201723
8 202123
9 201422
10
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More
201621
11 201718
12 202011
13 201711
14 202311
15 20189
16 20237
17
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives
20197
18 20197
19 20197
20 20224

About Aaron Sidford

Aaron Sidford is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Statistics and Probability, Computational Mechanics and Numerical Analysis, having authored 37 papers that have together received 546 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (27 papers), Markov Chains and Monte Carlo Methods (11 papers), Sparse and Compressive Sensing Techniques (9 papers), Stochastic Gradient Optimization Techniques (8 papers), Optimization and Search Problems (7 papers), Advanced Graph Theory Research (7 papers), Advanced Optimization Algorithms Research (7 papers) and Matrix Theory and Algorithms (4 papers). The work is most often cited by research in Computational Theory and Mathematics (318 citations), Numerical Analysis (93 citations), Computational Mathematics (10 citations), Computer Graphics and Computer-Aided Design (41 citations) and Statistics and Probability (75 citations). Aaron Sidford has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Yin Tat Lee, Jonathan A. Kelner, Oliver Hinder, Lorenzo Orecchia, Yair Carmon, John C. Duchi, Zeyuan Allen Zhu, Jan van den Brand, Yang P. Liu and Zhao Song. Their work appears in journals such as SIAM Journal on Computing, SIAM Journal on Optimization, Theory of Computing, Operations Research Letters and Conference on Learning Theory.

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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