| Cytoscape: a software environment for integrated models of biomolecular interaction networks P Shannon, A Markiel, O Ozier, NS Baliga, JT Wang, D Ramage, N Amin, ... Genome research 13 (11), 2498-2504, 2003 | 44505 | 2003 |
| Communication-efficient learning of deep networks from decentralized data B McMahan, E Moore, D Ramage, S Hampson, BA y Arcas Artificial intelligence and statistics, 1273-1282, 2017 | 20253 | 2017 |
| Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and trends® in machine learning 14 (1–2), 1-210, 2021 | 6438 | 2021 |
| Practical secure aggregation for privacy-preserving machine learning K Bonawitz, V Ivanov, B Kreuter, A Marcedone, HB McMahan, S Patel, ... proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017 | 3392 | 2017 |
| Towards federated learning at scale: System design K Bonawitz, H Eichner, W Grieskamp, D Huba, A Ingerman, V Ivanov, ... arXiv preprint arXiv:1902.01046, 2019 | 3284 | 2019 |
| Federated optimization: Distributed machine learning for on-device intelligence J Konečný, HB McMahan, D Ramage, P Richtárik arXiv preprint arXiv:1610.02527, 2016 | 2350 | 2016 |
| Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora D Ramage, D Hall, R Nallapati, CD Manning Proceedings of the 2009 conference on empirical methods in natural language …, 2009 | 1918 | 2009 |
| Federated learning for mobile keyboard prediction A Hard, K Rao, R Mathews, S Ramaswamy, F Beaufays, S Augenstein, ... arXiv preprint arXiv:1811.03604, 2018 | 1782 | 2018 |
| Learning differentially private recurrent language models HB McMahan, D Ramage, K Talwar, L Zhang arXiv preprint arXiv:1710.06963, 2017 | 1466 | 2017 |
| Characterizing microblogs with topic models D Ramage, S Dumais, D Liebling Proceedings of the international AAAI conference on web and social media 4 …, 2010 | 1096 | 2010 |
| Federated optimization: Distributed optimization beyond the datacenter J Konečný, B McMahan, D Ramage arXiv preprint arXiv:1511.03575, 2015 | 819 | 2015 |
| Federated learning: Collaborative machine learning without centralized training data B McMahan, D Ramage Google Research Blog 3, 2017 | 800 | 2017 |
| Applied federated learning: Improving google keyboard query suggestions T Yang, G Andrew, H Eichner, H Sun, W Li, N Kong, D Ramage, ... arXiv preprint arXiv:1812.02903, 2018 | 732 | 2018 |
| Practical secure aggregation for federated learning on user-held data K Bonawitz, V Ivanov, B Kreuter, A Marcedone, HB McMahan, S Patel, ... arXiv preprint arXiv:1611.04482, 2016 | 571 | 2016 |
| Social tag prediction P Heymann, D Ramage, H Garcia-Molina Proceedings of the 31st annual international ACM SIGIR conference on …, 2008 | 449 | 2008 |
| # TwitterSearch: a comparison of microblog search and web search J Teevan, D Ramage, MR Morris Proceedings of the fourth ACM international conference on Web search and …, 2011 | 422 | 2011 |
| Discrete distribution estimation under local privacy P Kairouz, K Bonawitz, D Ramage International Conference on Machine Learning, 2436-2444, 2016 | 384 | 2016 |
| Interpretation and trust: Designing model-driven visualizations for text analysis J Chuang, D Ramage, C Manning, J Heer Proceedings of the SIGCHI conference on human factors in computing systems …, 2012 | 354 | 2012 |
| Clustering the tagged web D Ramage, P Heymann, CD Manning, H Garcia-Molina Proceedings of the Second ACM International Conference on Web Search and …, 2009 | 352 | 2009 |
| Federated evaluation of on-device personalization K Wang, R Mathews, C Kiddon, H Eichner, F Beaufays, D Ramage arXiv preprint arXiv:1910.10252, 2019 | 346 | 2019 |
