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 | 42956 | 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 | 18177 | 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 | 5826 | 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 | 3137 | 2017 |
Towards federated learning at scale: Syste m design K Bonawitz arXiv preprint arXiv:1902.01046, 2019 | 3080 | 2019 |
Federated optimization: Distributed machine learning for on-device intelligence J Konečný, HB McMahan, D Ramage, P Richtárik arXiv preprint arXiv:1610.02527, 2016 | 2205 | 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 | 1894 | 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 | 1664 | 2018 |
Learning differentially private recurrent language models HB McMahan, D Ramage, K Talwar, L Zhang arXiv preprint arXiv:1710.06963, 2017 | 1366 | 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 | 1086 | 2010 |
Federated optimization: Distributed optimization beyond the datacenter J Konečný, B McMahan, D Ramage arXiv preprint arXiv:1511.03575, 2015 | 779 | 2015 |
Federated learning: Collaborative machine learning without centralized training data B McMahan, D Ramage Google Research Blog 3, 2017 | 772 | 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 | 691 | 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 | 530 | 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 | 369 | 2016 |
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 | 350 | 2009 |
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 | 349 | 2012 |
Federated evaluation of on-device personalization K Wang, R Mathews, C Kiddon, H Eichner, F Beaufays, D Ramage arXiv preprint arXiv:1910.10252, 2019 | 328 | 2019 |