László A. Végh

645 total citations
39 papers, 215 citations indexed

About

László A. Végh is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Economics and Econometrics. According to data from OpenAlex, László A. Végh has authored 39 papers receiving a total of 215 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computational Theory and Mathematics, 17 papers in Computer Networks and Communications and 8 papers in Economics and Econometrics. Recurrent topics in László A. Végh's work include Complexity and Algorithms in Graphs (21 papers), Optimization and Search Problems (14 papers) and Advanced Graph Theory Research (14 papers). László A. Végh is often cited by papers focused on Complexity and Algorithms in Graphs (21 papers), Optimization and Search Problems (14 papers) and Advanced Graph Theory Research (14 papers). László A. Végh collaborates with scholars based in United Kingdom, United States and Hungary. László A. Végh's co-authors include Joseph Cheriyan, Ola Svensson, András A. Benczúr, Daniel Dadush, András Frank, Neil Olver, Jugal Garg, Dániel Marx, Nikhil R. Devanur and Bernhard von Stengel and has published in prestigious journals such as Journal of the ACM, Mathematical Programming and SIAM Journal on Computing.

In The Last Decade

László A. Végh

33 papers receiving 201 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
László A. Végh United Kingdom 9 120 69 39 39 32 39 215
Christine T. Cheng United States 9 82 0.7× 55 0.8× 21 0.5× 35 0.9× 36 1.1× 28 207
Laurent Gourvès France 9 120 1.0× 61 0.9× 70 1.8× 51 1.3× 35 1.1× 30 223
Sana Ben Hamida France 7 127 1.1× 16 0.2× 42 1.1× 26 0.7× 162 5.1× 14 282
Nihal Pekergin France 8 80 0.7× 52 0.8× 27 0.7× 3 0.1× 22 0.7× 35 162
Édouard Wagneur Canada 8 62 0.5× 60 0.9× 20 0.5× 8 0.2× 13 0.4× 30 253
Riccardo Cambini Italy 11 163 1.4× 20 0.3× 26 0.7× 5 0.1× 11 0.3× 45 300
Danielle C. Tarraf United States 9 131 1.1× 32 0.5× 9 0.2× 7 0.2× 18 0.6× 38 256
Vsevolod Shneer United Kingdom 7 81 0.7× 133 1.9× 48 1.2× 4 0.1× 65 2.0× 17 326
Christian Posthoff Germany 8 72 0.6× 21 0.3× 13 0.3× 2 0.1× 77 2.4× 37 172
Carme Àlvarez Spain 8 102 0.8× 114 1.7× 10 0.3× 6 0.2× 64 2.0× 32 220

Countries citing papers authored by László A. Végh

Since Specialization
Citations

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

Fields of papers citing papers by László A. Végh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by László A. Végh. 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 László A. Végh. The network helps show where László A. Végh may publish in the future.

Co-authorship network of co-authors of László A. Végh

This figure shows the co-authorship network connecting the top 25 collaborators of László A. Végh. A scholar is included among the top collaborators of László A. Végh 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 László A. Végh. László A. Végh 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
1.
Tao, Yixin, et al.. (2025). Mode Connectivity in Auction Design. Mathematics of Operations Research. 51(1). 456–475. 1 indexed citations
2.
Peis, Britta, et al.. (2025). Faster Dynamic Auctions via Polymatroid Sum. LSE Research Online. 13(3). 1–47.
3.
Fujishige, Satoru, et al.. (2024). An update-and-stabilize framework for the minimum-norm-point problem. Mathematical Programming. 210(1-2). 281–311.
4.
Dadush, Daniel, et al.. (2024). A Strongly Polynomial Algorithm for Linear Programs with At Most Two Nonzero Entries per Row or Column. London School of Economics and Political Science Research Online (London School of Economics and Political Science). 1561–1572.
5.
Garg, Jugal, et al.. (2023). An Auction Algorithm for Market Equilibrium with Weak Gross Substitute Demands. London School of Economics and Political Science Research Online (London School of Economics and Political Science). 11(3-4). 1–24.
6.
Dadush, Daniel, et al.. (2023). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. Mathematical Programming. 204(1-2). 135–206. 4 indexed citations
7.
Garg, Jugal, et al.. (2023). Approximating Nash Social Welfare by Matching and Local Search. LSE Research Online. 1298–1310. 5 indexed citations
8.
Dadush, Daniel, et al.. (2022). An Accelerated Newton–Dinkelbach Method and Its Application to Two Variables per Inequality Systems. Mathematics of Operations Research. 1 indexed citations
9.
Allamigeon, Xavier, et al.. (2022). Interior point methods are not worse than Simplex. University of Twente Research Information. 267–277. 4 indexed citations
10.
Végh, László A., et al.. (2022). Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). Society for Industrial and Applied Mathematics eBooks. 9 indexed citations
11.
Dadush, Daniel, et al.. (2020). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. London School of Economics and Political Science Theses Online (London School of Economics and Political Science). 761–774. 6 indexed citations
12.
Garg, Jugal, et al.. (2019). Auction Algorithms for Market Equilibrium with Weak Gross Substitute\n Demands. arXiv (Cornell University).
13.
Svensson, Ola, et al.. (2017). Constant factor approximation for ATSP with two edge weights. Mathematical Programming. 172(1-2). 371–397. 3 indexed citations
14.
Végh, László A., et al.. (2015). The Cutting Plane Method is Polynomial for Perfect Matchings. Mathematics of Operations Research. 41(1). 23–48. 3 indexed citations
15.
Végh, László A.. (2014). A strongly polynomial algorithm for generalized flow maximization. 644–653. 4 indexed citations
16.
Cheriyan, Joseph & László A. Végh. (2013). Approximating Minimum-Cost k-Node Connected Subgraphs via Independence-Free Graphs. 30–39. 5 indexed citations
17.
18.
Végh, László A., et al.. (2012). The Cutting Plane Method Is Polynomial for Perfect Matchings. London School of Economics and Political Science Research Online (London School of Economics and Political Science). 5. 571–580. 3 indexed citations
19.
Végh, László A. & András A. Benczúr. (2008). Primal-dual approach for directed vertex connectivity augmentation and generalizations. ACM Transactions on Algorithms. 4(2). 1–21. 6 indexed citations
20.
Végh, László A. & András A. Benczúr. (2005). Primal-dual approach for directed vertex connectivity augmentation and generalizations. Symposium on Discrete Algorithms. 186–194. 3 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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