P
Praneeth Vepakomma
Researcher at Massachusetts Institute of Technology
Publications - 40
Citations - 4760
Praneeth Vepakomma is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Deep learning & Distance correlation. The author has an hindex of 14, co-authored 40 publications receiving 2038 citations. Previous affiliations of Praneeth Vepakomma include Motorola & Motorola Solutions.
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Advances and open problems in federated learning
Peter Kairouz,H. Brendan McMahan,Brendan Avent,Aurélien Bellet,Mehdi Bennis,Arjun Nitin Bhagoji,Kallista 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,Zaid Harchaoui,Chaoyang He,Lie He,Zhouyuan Huo,Ben Hutchinson,Justin Hsu,Martin Jaggi,Tara Javidi,Gauri Joshi,Mikhail Khodak,Jakub Konecní,Aleksandra Korolova,Farinaz Koushanfar,Sanmi Koyejo,Tancrède Lepoint,Yang Liu,Prateek Mittal,Mehryar Mohri,Richard Nock,Ayfer Ozgur,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 +58 more
TL;DR: In this article, the authors describe the state-of-the-art in the field of federated learning from the perspective of distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, and statistics.
Posted Content
Advances and Open Problems in Federated Learning
Peter Kairouz,H. Brendan McMahan,Brendan Avent,Aurélien Bellet,Mehdi Bennis,Arjun Nitin Bhagoji,Kallista 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,Zaid Harchaoui,Chaoyang He,Lie He,Zhouyuan Huo,Ben Hutchinson,Justin Hsu,Martin Jaggi,Tara Javidi,Gauri Joshi,Mikhail Khodak,Jakub Konečný,Aleksandra Korolova,Farinaz Koushanfar,Sanmi Koyejo,Tancrède Lepoint,Yang Liu,Prateek Mittal,Mehryar Mohri,Richard Nock,Ayfer Ozgur,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 +58 more
TL;DR: Motivated by the explosive growth in FL research, this paper discusses recent advances and presents an extensive collection of open problems and challenges.
Posted Content
Split learning for health: Distributed deep learning without sharing raw patient data
TL;DR: This paper compares performance and resource efficiency trade-offs of splitNN and other distributed deep learning methods like federated learning, large batch synchronous stochastic gradient descent and show highly encouraging results for splitNN.
Posted Content
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He,Songze Li,Jinhyun So,Mi Zhang,Hongyi Wang,Xiaoyang Wang,Praneeth Vepakomma,Abhishek Singh,Hang Qiu,Li Shen,Peilin Zhao,Kang Yan,Yang Liu,Ramesh Raskar,Qiang Yang,Murali Annavaram,A. Salman Avestimehr +16 more
TL;DR: FedML is introduced, an open research library and benchmark that facilitates the development of new federated learning algorithms and fair performance comparisons and can provide an efficient and reproducible means of developing and evaluating algorithms for the Federated learning research community.
Posted Content
Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic.
Ramesh Raskar,Isabel Schunemann,Rachel Barbar,Kristen Vilcans,Jim Gray,Praneeth Vepakomma,Suraj Kapa,Andrea Nuzzo,Rajiv Gupta,Alex Berke,Dazza Greenwood,Christian Keegan,Shriank Kanaparti,Robson Beaudry,David Stansbury,Beatriz Botero Arcila,Rishank Kanaparti,Vitor F. Pamplona,Francesco M. Benedetti,Alina Clough,Riddhiman Das,Kaushal Jain,Khahlil Louisy,Greg Nadeau,Vitor Pamplona,Steve Penrod,Yasaman Rajaee,Abhishek Singh,Greg Storm,John S. Werner +29 more
TL;DR: The different technological approaches to mobile-phone based contact-tracing to date are outlined and advanced security enhancing approaches that can mitigate these risks are described and trade-offs one must make are described.