Suivre
Alireza Fallah
Alireza Fallah
Ph.D. Candidate, MIT
Adresse e-mail validée de mit.edu - Page d'accueil
Titre
Citée par
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Année
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach
A Fallah, A Mokhtari, A Ozdaglar
Advances in Neural Information Processing Systems 33, 2020
581*2020
On the convergence theory of gradient-based model-agnostic meta-learning algorithms
A Fallah, A Mokhtari, A Ozdaglar
International Conference on Artificial Intelligence and Statistics, 1082-1092, 2020
1602020
Robust accelerated gradient methods for smooth strongly convex functions
NS Aybat, A Fallah, M Gurbuzbalaban, A Ozdaglar
SIAM Journal on Optimization 30 (1), 717-751, 2020
492020
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
NS Aybat, A Fallah, M Gurbuzbalaban, A Ozdaglar
Advances in Neural Information Processing Systems, 8523-8534, 2019
422019
On the convergence theory of debiased model-agnostic meta-reinforcement learning
A Fallah, K Georgiev, A Mokhtari, A Ozdaglar
Advances in Neural Information Processing Systems 34, 3096-3107, 2021
37*2021
Private Adaptive Gradient Methods for Convex Optimization
H Asi, J Duchi, A Fallah, O Javidbakht, K Talwar
International Conference on Machine Learning, 383-392, 2021
282021
Multidimensional Lévy white noise in weighted Besov spaces
J Fageot, A Fallah, M Unser
Stochastic Processes and their Applications 127 (5), 1599-1621, 2017
282017
Robust distributed accelerated stochastic gradient methods for multi-agent networks
A Fallah, M Gurbuzbalaban, A Ozdaglar, U Simsekli, L Zhu
arXiv preprint arXiv:1910.08701, 2019
26*2019
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks
A Fallah, A Mokhtari, A Ozdaglar
Advances in Neural Information Processing Systems 34, 2021
252021
An optimal multistage stochastic gradient method for minimax problems
A Fallah, A Ozdaglar, S Pattathil
2020 59th IEEE Conference on Decision and Control (CDC), 3573-3579, 2020
212020
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms
A Fallah, A Makhdoumi, A Malekian, A Ozdaglar
arXiv preprint arXiv:2201.03968, 2022
122022
Optimal adaptive testing for epidemic control: combining molecular and serology tests
D Acemoglu, A Fallah, A Giometto, D Huttenlocher, A Ozdaglar, F Parise, ...
arXiv preprint arXiv:2101.00773, 2021
122021
Sampling and distortion tradeoffs for indirect source retrieval
E Mohammadi, A Fallah, F Marvasti
IEEE Transactions on Information Theory 63 (11), 6833-6848, 2017
62017
A Wasserstein Minimax Framework for Mixed Linear Regression
T Diamandis, YC Eldar, A Fallah, F Farnia, A Ozdaglar
International Conference on Machine Learning, 2021
42021
Entropic compressibility of Lévy processes
J Fageot, A Fallah, T Horel
IEEE Transactions on Information Theory 68 (8), 4949-4963, 2022
22022
Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms
A Fallah, A Makhdoumi, A Malekian, AE Ozdaglar
Advances in Neural Information Processing Systems, 2022
12022
How Good Are Privacy Guarantees? Data Sharing, Privacy Preservation, and Platform Behavior
D Acemoglu, A Fallah, A Makhdoumi, A Malekian, AE Ozdaglar
Data Sharing, Privacy Preservation, and Platform Behavior (January 22, 2023), 2023
2023
Robust accelerated gradient methods for machine learning
A Fallah
Massachusetts Institute of Technology, 2019
2019
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Articles 1–18