default search action
Daniel Ramage
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c24]Eugene Bagdasarian, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage:
AirGapAgent: Protecting Privacy-Conscious Conversational Agents. CCS 2024: 3868-3882 - [i21]Shanshan Wu, Zheng Xu, Yanxiang Zhang, Yuanbo Zhang, Daniel Ramage:
Prompt Public Large Language Models to Synthesize Data for Private On-device Applications. CoRR abs/2404.04360 (2024) - [i20]Hubert Eichner, Daniel Ramage, Kallista A. Bonawitz, Dzmitry Huba, Tiziano Santoro, Brett McLarnon, Timon Van Overveldt, Nova Fallen, Peter Kairouz, Albert Cheu, Katharine Daly, Adrià Gascón, Marco Gruteser, Brendan McMahan:
Confidential Federated Computations. CoRR abs/2404.10764 (2024) - [i19]Eugene Bagdasaryan, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage:
Air Gap: Protecting Privacy-Conscious Conversational Agents. CoRR abs/2405.05175 (2024) - [i18]Katharine Daly, Hubert Eichner, Peter Kairouz, H. Brendan McMahan, Daniel Ramage, Zheng Xu:
Federated Learning in Practice: Reflections and Projections. CoRR abs/2410.08892 (2024) - 2023
- [i17]Yuanbo Zhang, Daniel Ramage, Zheng Xu, Yanxiang Zhang, Shumin Zhai, Peter Kairouz:
Private Federated Learning in Gboard. CoRR abs/2306.14793 (2023) - 2022
- [j3]Kallista A. Bonawitz, Peter Kairouz, Brendan McMahan, Daniel Ramage:
Federated learning and privacy. Commun. ACM 65(4): 90-97 (2022) - [c23]Virat Shejwalkar, Amir Houmansadr, Peter Kairouz, Daniel Ramage:
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning. SP 2022: 1354-1371 - 2021
- [j2]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j1]Kallista A. Bonawitz, Peter Kairouz, Brendan McMahan, Daniel Ramage:
Federated Learning and Privacy: Building privacy-preserving systems for machine learning and data science on decentralized data. ACM Queue 19(5): 87-114 (2021) - [i16]Virat Shejwalkar, Amir Houmansadr, Peter Kairouz, Daniel Ramage:
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Federated Learning. CoRR abs/2108.10241 (2021) - 2020
- [c22]Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas:
Generative Models for Effective ML on Private, Decentralized Datasets. ICLR 2020 - [c21]Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun:
Context Aware Local Differential Privacy. ICML 2020: 52-62 - [i15]Daniel Ramage, Christopher D. Manning, Daniel A. McFarland:
Mapping Three Decades of Intellectual Change in Academia. CoRR abs/2004.01291 (2020)
2010 – 2019
- 2019
- [c20]Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konecný, Stefano Mazzocchi, Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, Jason Roselander:
Towards Federated Learning at Scale: System Design. SysML 2019 - [i14]Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konecný, Stefano Mazzocchi, H. Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, Jason Roselander:
Towards Federated Learning at Scale: System Design. CoRR abs/1902.01046 (2019) - [i13]Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage:
Federated Evaluation of On-device Personalization. CoRR abs/1910.10252 (2019) - [i12]Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun:
Context-Aware Local Differential Privacy. CoRR abs/1911.00038 (2019) - [i11]Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas:
Generative Models for Effective ML on Private, Decentralized Datasets. CoRR abs/1911.06679 (2019) - [i10]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - 2018
- [c19]H. Brendan McMahan, Daniel Ramage, Kunal Talwar, Li Zhang:
Learning Differentially Private Recurrent Language Models. ICLR (Poster) 2018 - [i9]Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage:
Federated Learning for Mobile Keyboard Prediction. CoRR abs/1811.03604 (2018) - [i8]Timothy Yang, Galen Andrew, Hubert Eichner, Haicheng Sun, Wei Li, Nicholas Kong, Daniel Ramage, Françoise Beaufays:
Applied Federated Learning: Improving Google Keyboard Query Suggestions. CoRR abs/1812.02903 (2018) - 2017
- [c18]Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas:
Communication-Efficient Learning of Deep Networks from Decentralized Data. AISTATS 2017: 1273-1282 - [c17]Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth:
Practical Secure Aggregation for Privacy-Preserving Machine Learning. CCS 2017: 1175-1191 - [i7]H. Brendan McMahan, Daniel Ramage, Kunal Talwar, Li Zhang:
Learning Differentially Private Language Models Without Losing Accuracy. CoRR abs/1710.06963 (2017) - [i6]Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth:
Practical Secure Aggregation for Privacy Preserving Machine Learning. IACR Cryptol. ePrint Arch. 2017: 281 (2017) - 2016
- [c16]Peter Kairouz, Kallista A. Bonawitz, Daniel Ramage:
Discrete Distribution Estimation under Local Privacy. ICML 2016: 2436-2444 - [i5]H. Brendan McMahan, Eider Moore, Daniel Ramage, Blaise Agüera y Arcas:
Federated Learning of Deep Networks using Model Averaging. CoRR abs/1602.05629 (2016) - [i4]Peter Kairouz, Kallista A. Bonawitz, Daniel Ramage:
Discrete Distribution Estimation under Local Privacy. CoRR abs/1602.07387 (2016) - [i3]Jakub Konecný, H. Brendan McMahan, Daniel Ramage, Peter Richtárik:
Federated Optimization: Distributed Machine Learning for On-Device Intelligence. CoRR abs/1610.02527 (2016) - [i2]Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth:
Practical Secure Aggregation for Federated Learning on User-Held Data. CoRR abs/1611.04482 (2016) - 2015
- [i1]Jakub Konecný, Brendan McMahan, Daniel Ramage:
Federated Optimization: Distributed Optimization Beyond the Datacenter. CoRR abs/1511.03575 (2015) - 2012
- [c15]Jason Chuang, Daniel Ramage, Christopher D. Manning, Jeffrey Heer:
Interpretation and trust: designing model-driven visualizations for text analysis. CHI 2012: 443-452 - 2011
- [b1]Daniel Ramage:
Studying people, organizations, and the web with statistical text models. Stanford University, USA, 2011 - [c14]Daniel Ramage, Christopher D. Manning, Susan T. Dumais:
Partially labeled topic models for interpretable text mining. KDD 2011: 457-465 - [c13]Nikhil Johri, Daniel Ramage, Daniel A. McFarland, Daniel Jurafsky:
A Study of Academic Collaborations in Computational Linguistics using a Latent Mixture of Authors Model. LaTeCH@ACL 2011: 124-132 - [c12]Jaime Teevan, Daniel Ramage, Meredith Ringel Morris:
#TwitterSearch: a comparison of microblog search and web search. WSDM 2011: 35-44 - 2010
- [c11]Daniel Ramage, Susan T. Dumais, Daniel J. Liebling:
Characterizing Microblogs with Topic Models. ICWSM 2010
2000 – 2009
- 2009
- [c10]Daniel Ramage, David Hall, Ramesh Nallapati, Christopher D. Manning:
Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. EMNLP 2009: 248-256 - [c9]Daniel Ramage, Anna N. Rafferty, Christopher D. Manning:
Random Walks for Text Semantic Similarity. Graph-based Methods for Natural Language Processing 2009: 23-31 - [c8]Eric Yeh, Daniel Ramage, Christopher D. Manning, Eneko Agirre, Aitor Soroa:
WikiWalk: Random walks on Wikipedia for Semantic Relatedness. Graph-based Methods for Natural Language Processing 2009: 41-49 - [c7]Daniel Ramage, Paul Heymann, Christopher D. Manning, Hector Garcia-Molina:
Clustering the tagged web. WSDM 2009: 54-63 - 2008
- [c6]Paul Heymann, Daniel Ramage, Hector Garcia-Molina:
Social tag prediction. SIGIR 2008: 531-538 - 2007
- [c5]Marie-Catherine de Marneffe, Trond Grenager, Bill MacCartney, Daniel M. Cer, Daniel Ramage, Chloé Kiddon, Christopher D. Manning:
Robust Graph Alignment Methods for Textual Inference and Machine Reading. AAAI Spring Symposium: Machine Reading 2007: 36-42 - [c4]Nathanael Chambers, Daniel M. Cer, Trond Grenager, David Hall, Chloé Kiddon, Bill MacCartney, Marie-Catherine de Marneffe, Daniel Ramage, Eric Yeh, Christopher D. Manning:
Learning Alignments and Leveraging Natural Logic. ACL-PASCAL@ACL 2007: 165-170 - [c3]Thad Hughes, Daniel Ramage:
Lexical Semantic Relatedness with Random Graph Walks. EMNLP-CoNLL 2007: 581-589 - [c2]Daniel Ramage, Adam J. Oliner:
RA: ResearchAssistant for the computational sciences. Experimental Computer Science 2007: 19 - 2002
- [c1]danah boyd, Hyun-Yeul Lee, Daniel Ramage, Judith S. Donath:
Developing Legible Visualizations for Online Social Spaces. HICSS 2002: 115
Coauthor Index
aka: Brendan McMahan
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-11 20:44 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint