Eider Moore
Impact in
- Artificial Intelligence top 0.5%
- Privacy-Preserving Technologies in Data
- Stochastic Gradient Optimization Techniques
- Cryptography and Data Security
- Internet Traffic Analysis and Secure E-voting
- Adversarial Robustness in Machine Learning
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- Mobile Crowdsensing and Crowdsourcing
Papers in
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- Functional Brain Connectivity Studies 3
- EEG and Brain-Computer Interfaces 1
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- Privacy-Preserving Technologies in Data 1
- Sentiment Analysis and Opinion Mining 1
- Hate Speech and Cyberbullying Detection 1
- Co-authors
- H. Brendan McMahan (1 shared paper)Daniel Ramage (1 shared paper)Blaise Agüera y Arcas (1 shared paper)Hao Ma (1 shared paper)Gargi Ghosh (1 shared paper)Xiaochang Peng (1 shared paper)Fan Yang (1 shared paper)Andrew V. Poliakov (3 shared papers)
- Journals
- Neuroinformatics (1 paper)NeuroImage (1 paper)BMC Bioinformatics (1 paper)Journal of Neuroscience Methods (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesAustriaIsrael
In The Last Decade
Eider Moore
6 papers receiving 2.6k citations
Eider Moore's Hit Papers
Peers
Comparison fields: 5 of 121
- Artificial Intelligence 2.2k
- Computer Science Applications 346
- Health Informatics 72
- Computer Networks and Communications 641
- Information Systems 366
Countries citing papers authored by Eider Moore
This map shows the geographic impact of Eider Moore'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 Eider Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eider Moore more than expected).
Fields of papers citing papers by Eider Moore
This network shows the impact of papers produced by Eider Moore. 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 Eider Moore. The network helps show where Eider Moore may publish in the future.
Co-authors
The 20 scholars most cited alongside Eider Moore, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Communication-Efficient Learning of Deep Networks from Decentralized Data Hit paper breakdown → | 2016 | 2635 |
| 2 | 2019 | 50 | |
| 3 | 2010 | 17 | |
| 4 | 2007 | 12 | |
| 5 | 2007 | 9 | |
| 6 | 2002 | 9 |
About Eider Moore
Eider Moore is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition, Transportation and Radiology, Nuclear Medicine and Imaging, having authored 6 papers that have together received 2.7k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (3 papers), Privacy-Preserving Technologies in Data (1 paper), Sentiment Analysis and Opinion Mining (1 paper), EEG and Brain-Computer Interfaces (1 paper), Medical Image Segmentation Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Hate Speech and Cyberbullying Detection (1 paper). The work is most often cited by research in Artificial Intelligence (2.2k citations), Computer Science Applications (346 citations), Health Informatics (72 citations), Computer Networks and Communications (641 citations) and Information Systems (366 citations). Eider Moore has collaborated with scholars based in United States, Austria and Israel. Frequent co-authors include H. Brendan McMahan, Daniel Ramage, Blaise Agüera y Arcas, Hao Ma, Gargi Ghosh, Xiaochang Peng, Fan Yang, Andrew V. Poliakov, James F. Brinkley and Peter Lincoln. Their work appears in journals such as Neuroinformatics, NeuroImage, BMC Bioinformatics, Journal of Neuroscience Methods and arXiv (Cornell 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.