Brendan McMahan

569 total citations
9 papers, 200 citations indexed

About

Brendan McMahan is a scholar working on Artificial Intelligence, Computer Networks and Communications and Management Science and Operations Research. According to data from OpenAlex, Brendan McMahan has authored 9 papers receiving a total of 200 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Computer Networks and Communications and 3 papers in Management Science and Operations Research. Recurrent topics in Brendan McMahan's work include Cryptography and Data Security (3 papers), Machine Learning and Algorithms (3 papers) and Privacy-Preserving Technologies in Data (3 papers). Brendan McMahan is often cited by papers focused on Cryptography and Data Security (3 papers), Machine Learning and Algorithms (3 papers) and Privacy-Preserving Technologies in Data (3 papers). Brendan McMahan collaborates with scholars based in United States. Brendan McMahan's co-authors include M. J. V. Streeter, Kallista Bonawitz, Peter Kairouz, Daniel Ramage, John C. Duchi, Michael I. Jordan, Anupam Gupta, Andreas Krause, Carlos Guestrin and Blake Woodworth and has published in prestigious journals such as Communications of the ACM, Queue and OpenBU/Boston University Institutional Repository (Boston University).

In The Last Decade

Brendan McMahan

9 papers receiving 189 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Brendan McMahan United States	7	142	54	34	32	27	9	200
Yevgeny Seldin Germany	10	215 1.5×	41 0.8×	25 0.7×	126 3.9×	21 0.8×	30	266
Sai Praneeth Karimireddy Switzerland	8	273 1.9×	66 1.2×	49 1.4×	5 0.2×	27 1.0×	19	301
Yaochen Hu Canada	10	180 1.3×	83 1.5×	39 1.1×	16 0.5×	4 0.1×	15	276
Weiqi Li China	9	100 0.7×	59 1.1×	86 2.5×	11 0.3×	6 0.2×	24	204
Yangyu Tao China	7	177 1.2×	111 2.1×	70 2.1×	9 0.3×	7 0.3×	14	316
Kristian Woodsend United Kingdom	11	437 3.1×	13 0.2×	59 1.7×	13 0.4×	17 0.6×	16	493
Arjun Nitin Bhagoji United States	7	218 1.5×	52 1.0×	29 0.9×	4 0.1×	4 0.1×	18	249
Tiansheng Yao United States	8	248 1.7×	21 0.4×	126 3.7×	50 1.6×	33 1.2×	8	363

Countries citing papers authored by Brendan McMahan

Since Specialization

Citations

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

Fields of papers citing papers by Brendan McMahan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brendan McMahan

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

All Works

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9 of 9 papers shown

Ponomareva, Natalia, et al.. (2023). How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. 5823–5824. 6 indexed citations

Bonawitz, Kallista, Peter Kairouz, Brendan McMahan, & Daniel Ramage. (2022). Federated learning and privacy. Communications of the ACM. 65(4). 90–97. 19 indexed citations

Bonawitz, Kallista, Peter Kairouz, Brendan McMahan, & Daniel Ramage. (2021). Federated Learning and Privacy. Queue. 19(5). 87–114. 43 indexed citations

Woodworth, Blake, Jialei Wang, Adam Smith, Brendan McMahan, & Nati Srebro. (2018). Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization. OpenBU/Boston University Institutional Repository (Boston University). 31. 8496–8506. 16 indexed citations

McMahan, Brendan & M. J. V. Streeter. (2014). Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning. Neural Information Processing Systems. 27. 2915–2923. 54 indexed citations

McMahan, Brendan & Jacob Abernethy. (2013). Minimax Optimal Algorithms for Unconstrained Linear Optimization. arXiv (Cornell University). 26. 2724–2732. 4 indexed citations

Duchi, John C., Michael I. Jordan, & Brendan McMahan. (2013). Estimation, Optimization, and Parallelism when Data is Sparse. Neural Information Processing Systems. 26. 2832–2840. 27 indexed citations

McMahan, Brendan & M. J. V. Streeter. (2012). No-Regret Algorithms for Unconstrained Online Convex Optimization. Neural Information Processing Systems. 25. 2402–2410. 6 indexed citations

Krause, Andreas, Brendan McMahan, Carlos Guestrin, & Anupam Gupta. (2007). Selecting Observations against Adversarial Objectives. Neural Information Processing Systems. 20. 777–784. 25 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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