Antonious M. Girgis

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 32

Top Topics

Multicast Routing

Differential Privacy

Wireless Networks

Learning Scheme

Top Venues

IEEE J. Sel. Areas Inf. Theory

IEEE Trans. Inf. Theory

Publications

Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil
Learning from straggler clients in federated learning. CoRR (2024)
Antonious M. Girgis, Suhas N. Diggavi
Multi-Message Shuffled Privacy in Federated Learning. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi
Differentially Private Stochastic Linear Bandits: (Almost) for Free. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy. ICLR (2023)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
Fundamental Limits of Cache-Aided MIMO Wireless Networks. IEEE Trans. Inf. Theory 69 (6) (2023)
Antonious M. Girgis, Suhas N. Diggavi
Multi-Message Shuffled Privacy in Federated Learning. CoRR (2023)
Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy. CoRR (2022)
Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi
Differentially Private Stochastic Linear Bandits: (Almost) for Free. CoRR (2022)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Distributed User-Level Private Mean Estimation. ISIT (2022)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Differentially Private Federated Learning with Shuffling and Client Self-Sampling. ISIT (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz
On the Renyi Differential Privacy of the Shuffle Model. CoRR (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning. NeurIPS (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs. IEEE J. Sel. Areas Inf. Theory 2 (1) (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
Shuffled Model of Differential Privacy in Federated Learning. AISTATS (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz
On the Rényi Differential Privacy of the Shuffle Model. CCS (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning. CoRR (2021)
Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri, Christina Fragouli, Suhas N. Diggavi
Successive Refinement of Privacy. CoRR (2020)
Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri, Christina Fragouli, Suhas N. Diggavi
Successive Refinement of Privacy. IEEE J. Sel. Areas Inf. Theory 1 (3) (2020)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Hiding Identities: Estimation Under Local Differential Privacy. ISIT (2020)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs. CoRR (2020)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
Coded Caching and Spatial Multiplexing Gains in MIMO Interference Networks. WCNC (2019)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
Fundamental Limits of Memory-Latency Tradeoff in Fog Radio Access Networks Under Arbitrary Demands. IEEE Trans. Wirel. Commun. 18 (8) (2019)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
A Converse Bound for Cache-Aided Interference Networks. ACSSC (2018)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
A Converse Bound for Cache-Aided Interference Networks. CoRR (2018)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
Degrees of Freedom of Interference Networks with Transmitter-Side Caches. CoRR (2017)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
Decentralized Coded Caching in Wireless Networks: Trade-off between Storage and Latency. CoRR (2017)
Antonious M. Girgis, Özgür Erçetin, Mohammed Nafie, Tamer A. ElBatt
Decentralized coded caching in wireless networks: Trade-off between storage and latency. ISIT (2017)
Antonious M. Girgis, Amr El-Keyi, Mohammed Nafie, Ramy H. Gohary
Proactive Location-Based Scheduling of Delay-Constrained Traffic Over Fading Channels. CoRR (2016)
Antonious M. Girgis, Amr El-Keyi, Mohammed Nafie, Ramy H. Gohary
Proactive Location-Based Scheduling of Delay-Constrained Traffic over Fading Channels. VTC Fall (2016)
Antonious M. Girgis, Amr El-Keyi, Mohammed Nafie
Optimal Energy Allocation for Delay-Constrained Traffic over Fading Multiple Access Channels. GLOBECOM (2016)
Antonious M. Girgis, Amr El-Keyi, Mohammed Nafie
Optimal Energy Allocation For Delay-Constrained Traffic Over Fading Multiple Access Channels. CoRR (2016)