Kallista A. Bonawitz

24 papers A* 4A 1Misc 1Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Confidential Federated Computations. CoRR 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
2022	J	`jnl`	Federated Select: A Primitive for Communication- and Memory-Efficient Federated Learning. CoRR Zachary Charles, Kallista A. Bonawitz, Stanislav Chiknavaryan, Brendan McMahan, Blaise Agüera y Arcas
2022	J	`jnl`	Federated learning and privacy. Commun. ACM Kallista A. Bonawitz, Peter Kairouz, Brendan McMahan, Daniel Ramage
2022	J	`jnl`	Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation. Proc. Priv. Enhancing Technol. Eugene Bagdasaryan, Peter Kairouz, Stefan Mellem, Adrià Gascón, Kallista A. Bonawitz, Deborah Estrin, Marco Gruteser
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 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
2021	J	`jnl`	Federated Learning and Privacy: Building privacy-preserving systems for machine learning and data science on decentralized data. ACM Queue Kallista A. Bonawitz, Peter Kairouz, Brendan McMahan, Daniel Ramage
2021	J	`jnl`	Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation. CoRR Eugene Bagdasaryan, Peter Kairouz, Stefan Mellem, Adrià Gascón, Kallista A. Bonawitz, Deborah Estrin, Marco Gruteser
2020	A*	`conf`	Context Aware Local Differential Privacy. ICML Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun
2020	A*	`conf`	Secure Single-Server Aggregation with (Poly)Logarithmic Overhead. CCS James Henry Bell, Kallista A. Bonawitz, Adrià Gascón, Tancrède Lepoint, Mariana Raykova
2020	J	`jnl`	Secure Single-Server Aggregation with (Poly)Logarithmic Overhead. IACR Cryptol. ePrint Arch. James Bell, Kallista A. Bonawitz, Adrià Gascón, Tancrède Lepoint, Mariana Raykova
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR 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
2019	J	`jnl`	Context-Aware Local Differential Privacy. CoRR Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun
2019	Misc	`conf`	Federated Learning with Autotuned Communication-Efficient Secure Aggregation. ACSSC Kallista A. Bonawitz, Fariborz Salehi, Jakub Konecný, Brendan McMahan, Marco Gruteser
2019	J	`jnl`	Federated Learning with Autotuned Communication-Efficient Secure Aggregation. CoRR Kallista A. Bonawitz, Fariborz Salehi, Jakub Konecný, Brendan McMahan, Marco Gruteser
2019	—	`conf`	Towards Federated Learning at Scale: System Design. SysML 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
2019	J	`jnl`	Towards Federated Learning at Scale: System Design. CoRR 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
2017	J	`jnl`	Practical Secure Aggregation for Privacy Preserving Machine Learning. IACR Cryptol. ePrint Arch. Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth
2017	A*	`conf`	Practical Secure Aggregation for Privacy-Preserving Machine Learning. CCS Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth
2016	A*	`conf`	Discrete Distribution Estimation under Local Privacy. ICML Peter Kairouz, Kallista A. Bonawitz, Daniel Ramage
2016	J	`jnl`	Discrete Distribution Estimation under Local Privacy. CoRR Peter Kairouz, Kallista A. Bonawitz, Daniel Ramage
2016	J	`jnl`	Practical Secure Aggregation for Federated Learning on User-Held Data. CoRR Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth
2012	J	`jnl`	Church: a language for generative models CoRR Noah D. Goodman, Vikash Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. Tenenbaum
2008	A	`conf`	Church: a language for generative models. UAI Noah D. Goodman, Vikash K. Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. Tenenbaum
2008	—	`—`	Composable probabilistic inference with BLAISE. Kallista A. Bonawitz