Brendan McMahan
- Artificial Intelligence top 10%
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Management Science and Operations Research
- Computational Mechanics
- Co-authors
- M. J. V. StreeterKallista BonawitzDaniel RamagePeter KairouzJohn C. DuchiMichael I. JordanAnupam GuptaAndreas Krause
- Topics
- Cryptography and Data Security (3 papers)Machine Learning and Algorithms (3 papers)Privacy-Preserving Technologies in Data (3 papers)
- Journals
- Communications of the ACMQueueOpenBU/Boston University Institutional Repository (Boston University)
- Partner nations
- United States
In The Last Decade
Brendan McMahan
9 papers receiving 189 citations
Peers
Comparison fields: 5 of 49
- Artificial Intelligence 142
- Computer Networks and Communications 54
- Computer Vision and Pattern Recognition 34
- Management Science and Operations Research 32
- Computational Mechanics 27
Countries citing papers authored by Brendan McMahan
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 19 | |
| 3 | 43 | |
| 4 | 16 | |
| 5 | Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning | 54 |
| 6 | Estimation, Optimization, and Parallelism when Data is Sparse | 27 |
| 7 | Minimax Optimal Algorithms for Unconstrained Linear Optimization | 4 |
| 8 | No-Regret Algorithms for Unconstrained Online Convex Optimization | 6 |
| 9 | Selecting Observations against Adversarial Objectives | 25 |
About Brendan McMahan
Brendan McMahan is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications, having authored 9 papers that have together received 200 indexed citations. Recurring topics across this work include Cryptography and Data Security (3 papers), Machine Learning and Algorithms (3 papers) and Privacy-Preserving Technologies in Data (3 papers). The work is most often cited by research in Artificial Intelligence (142 citations), Health Informatics (5 citations) and Management Science and Operations Research (32 citations). Brendan McMahan has collaborated with scholars based in United States. Frequent co-authors include M. J. V. Streeter, Kallista Bonawitz, Daniel Ramage, Peter Kairouz, John C. Duchi, Michael I. Jordan, Anupam Gupta, Andreas Krause, Carlos Guestrin and Blake Woodworth. Their work appears in journals such as Communications of the ACM, Queue and OpenBU/Boston University Institutional Repository (Boston University).
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.