Antonious M. Girgis

Researcher, Google DeepMind

Joined

May 2021

Names

Antonious M. Girgis (Preferred)

Emails

****@g.ucla.edu (Confirmed)

Personal Links

Homepage

Google Scholar

DBLP

Career & Education History

Researcher

Google DeepMind (google.com)

2023 – Present

PhD student

Electrical and Computer Engineering, University of California, Los Angeles (ucla.edu)

2018 – 2023

MS student

Nile University (nu.edu)

2015 – 2018

Undergrad student

Cairo University (cu.edu.eg)

2009 – 2014

Advisors, Relations & Conflicts

No relations added

Expertise

No areas of expertise listed

Publications

Distributed Mean Estimation for Multi-Message Shuffled Privacy
Antonious M. Girgis, Suhas Diggavi
- FL-ICML 2023
- Readers: Everyone
On the rényi differential privacy of the shuffle model
Antonious M. Girgis, Deepesh Data, Suhas Diggavi, Ananda Theertha Suresh, Peter Kairouz
- 21 Apr 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Multi-Message Shuffled Privacy in Federated Learning
Antonious M. Girgis, Suhas N. Diggavi
- 2023 (modified: 14 Apr 2023)
- CoRR 2023
- Readers: Everyone
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas Diggavi
- Published: 01 Feb 2023, Last Modified: 02 Mar 2023
- ICLR 2023 poster
- Readers: Everyone
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy
Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
- 2022 (modified: 14 Apr 2023)
- CoRR 2022
- Readers: Everyone
Distributed User-Level Private Mean Estimation
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
- 2022 (modified: 14 Apr 2023)
- ISIT 2022
- Readers: Everyone
Differentially Private Stochastic Linear Bandits: (Almost) for Free
Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi
- 2022 (modified: 14 Apr 2023)
- CoRR 2022
- Readers: Everyone
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning
Antonious M. Girgis, Deepesh Data, Suhas Diggavi
- Published: 09 Nov 2021, Last Modified: 05 May 2023
- NeurIPS 2021 Poster
- Readers: Everyone
A Field Guide to Federated Optimization
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 et al. (33 additional authors not shown)
- 2021 (modified: 28 Jul 2021)
- CoRR 2021
- Readers: Everyone
Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
- 2021 (modified: 14 Apr 2023)
- IEEE J. Sel. Areas Inf. Theory 2021
- Readers: Everyone

View all 31 publications

Co-Authors

View all 62 co-authors