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Private Adaptive Gradient Methods for Convex Optimization


Jun 25, 2021
Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

* To appear in 38th International Conference on Machine Learning (ICML 2021) 

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A Wasserstein Minimax Framework for Mixed Linear Regression


Jun 16, 2021
Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar

* To appear in 38th International Conference on Machine Learning (ICML 2021) 

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Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks


Feb 07, 2021
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar


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Personalized Federated Learning: A Meta-Learning Approach


Feb 19, 2020
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar


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An Optimal Multistage Stochastic Gradient Method for Minimax Problems


Feb 13, 2020
Alireza Fallah, Asuman Ozdaglar, Sarath Pattathil


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Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning


Feb 12, 2020
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar


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Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks


Nov 15, 2019
Alireza Fallah, Mert Gurbuzbalaban, Asuman Ozdaglar, Umut Simsekli, Lingjiong Zhu


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On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms


Sep 25, 2019
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar

* 33 pages 

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A Universally Optimal Multistage Accelerated Stochastic Gradient Method


Jan 25, 2019
Necdet Serhat Aybat, Alireza Fallah, Mert Gurbuzbalaban, Asuman Ozdaglar

* 20 pages, 12 figures 

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