Warren Schudy

710 total citations
12 papers, 228 citations indexed

About

Warren Schudy is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Warren Schudy has authored 12 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Theory and Mathematics, 4 papers in Artificial Intelligence and 3 papers in Management Science and Operations Research. Recurrent topics in Warren Schudy's work include Complexity and Algorithms in Graphs (6 papers), Random Matrices and Applications (2 papers) and Machine Learning and Algorithms (2 papers). Warren Schudy is often cited by papers focused on Complexity and Algorithms in Graphs (6 papers), Random Matrices and Applications (2 papers) and Machine Learning and Algorithms (2 papers). Warren Schudy collaborates with scholars based in United States, Switzerland and Germany. Warren Schudy's co-authors include Claire Kenyon-Mathieu, Micha Elsner, Claire Mathieu, Maxim Sviridenko, Vahab Mirrokni, Ocan Sankur, Kay H. Brodersen, Jean Pouget-Abadie, Soheil Behnezhad and Hossein Esfandiari and has published in prestigious journals such as Proceedings of the VLDB Endowment, ArXiv.org and Symposium on Discrete Algorithms.

In The Last Decade

Warren Schudy

11 papers receiving 215 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Warren Schudy United States 8 94 77 57 52 45 12 228
Anastasios Sidiropoulos United States 11 59 0.6× 183 2.4× 30 0.5× 22 0.4× 101 2.2× 49 343
Enjian Bai China 9 88 0.9× 18 0.2× 90 1.6× 41 0.8× 54 1.2× 43 295
T. Feder United States 7 59 0.6× 108 1.4× 20 0.4× 29 0.6× 67 1.5× 8 209
Eden Chlamtáč United States 7 72 0.8× 212 2.8× 29 0.5× 15 0.3× 85 1.9× 15 294
Steve Chien United States 8 119 1.3× 61 0.8× 117 2.1× 61 1.2× 116 2.6× 12 432
Claire Kenyon-Mathieu United States 6 65 0.7× 98 1.3× 59 1.0× 49 0.9× 72 1.6× 9 196
Michael Soltys United States 10 90 1.0× 100 1.3× 112 2.0× 10 0.2× 55 1.2× 31 334
Rudolf Berghammer Germany 10 241 2.6× 174 2.3× 48 0.8× 62 1.2× 74 1.6× 61 359
Yuval Filmus Israel 10 122 1.3× 157 2.0× 38 0.7× 28 0.5× 78 1.7× 53 300
Boutheina Ben Yaghlane Tunisia 9 149 1.6× 37 0.5× 56 1.0× 6 0.1× 43 1.0× 34 247

Countries citing papers authored by Warren Schudy

Since Specialization
Citations

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

Fields of papers citing papers by Warren Schudy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Warren Schudy

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

All Works

12 of 12 papers shown
1.
Behnezhad, Soheil, Laxman Dhulipala, Hossein Esfandiari, et al.. (2020). Parallel graph algorithms in constant adaptive rounds. Proceedings of the VLDB Endowment. 13(13). 3588–3602. 5 indexed citations
2.
Pouget-Abadie, Jean, et al.. (2019). Variance Reduction in Bipartite Experiments through Correlation Clustering. Neural Information Processing Systems. 32. 13288–13298. 10 indexed citations
3.
Schudy, Warren & Maxim Sviridenko. (2012). Concentration and moment inequalities for polynomials of independent random variables. Symposium on Discrete Algorithms. 437–446. 13 indexed citations
4.
Sankur, Ocan, et al.. (2010). Online Correlation Clustering. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 573–584. 9 indexed citations
5.
Mathieu, Claire & Warren Schudy. (2010). Correlation Clustering with Noisy Input. 712–728. 13 indexed citations
6.
Karpiński, Marek & Warren Schudy. (2009). Linear time approximation schemes for the Gale-Berlekamp game and related minimization problems. ArXiv.org. 15. 313–322.
7.
Elsner, Micha & Warren Schudy. (2009). Bounding and comparing methods for correlation clustering beyond ILP. 19–27. 42 indexed citations
8.
Greenwald, Amy, Zheng Li, & Warren Schudy. (2008). More Efficient Internal-Regret-Minimizing Algorithms.. Conference on Learning Theory. 239–250. 1 indexed citations
9.
Mathieu, Claire & Warren Schudy. (2008). Yet another algorithm for dense max cut: go greedy. 176–182. 4 indexed citations
10.
11.
Kenyon-Mathieu, Claire & Warren Schudy. (2007). How to rank with few errors. 95–103. 106 indexed citations
12.
Kenyon-Mathieu, Claire & Warren Schudy. (2006). How to rank with few errors: A PTAS for Weighted Feedback Arc Set on Tournaments.. Electronic colloquium on computational complexity. 13. 12 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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