Richard Beigel

3.4k citations
114 papers · 2.4k · h-index 29

Impact in

    • Complexity and Algorithms in Graphs
    • Advanced Graph Theory Research
    • Computability, Logic, AI Algorithms
    • semigroups and automata theory
    • Machine Learning and Algorithms
    • Algorithms and Data Compression
    • Cryptography and Data Security

Papers in

Richard Beigel

108 papers receiving 2.2k citations

Peers

Richard Beigel
Comparison fields: 5 of 77
  • Computational Theory and Mathematics 1.8k
  • Artificial Intelligence 1.4k
  • Discrete Mathematics and Combinatorics 119
  • Computational Mathematics 11
  • Computer Networks and Communications 409
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Citations per field
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Citations per year

Countries citing papers authored by Richard Beigel

Since Specialization
Citations

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

Fields of papers citing papers by Richard Beigel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1991125
2 1994122
3 1994113
4
OC1: randomized induction of oblique decision trees
1993107
5 200497
6 200293
7 199287
8 199186
9 199580
10 199478
11
Finding maximum independent sets in sparse and general graphs
199975
12 199471
13
Query-limited reducibilities
198857
14 199153
15 199351
16 200448
17 199546
18 200242
19 199339
20 199439

About Richard Beigel

Richard Beigel is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Hardware and Architecture, having authored 114 papers that have together received 2.4k indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (56 papers), Computability, Logic, AI Algorithms (33 papers), semigroups and automata theory (26 papers), Algorithms and Data Compression (18 papers), Machine Learning and Algorithms (18 papers), Advanced Graph Theory Research (17 papers), Optimization and Search Problems (10 papers) and DNA and Biological Computing (10 papers). The work is most often cited by research in Computational Theory and Mathematics (1.8k citations), Artificial Intelligence (1.4k citations), Discrete Mathematics and Combinatorics (119 citations), Computational Mathematics (11 citations) and Computer Networks and Communications (409 citations). Richard Beigel has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Daniel A. Spielman, Steven Rudich, Nick Reingold, David Eppstein, John T. Gill, Jun Tarui, William I. Gasarch, Simon Kasif, James Aspnes and Merrick L. Furst. Their work appears in journals such as Computational Complexity, Theoretical Computer Science, SIAM Journal on Computing, Information and Computation and Journal of Symbolic Logic.

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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