Thesis

• Robust Accelerated Gradient Methods for Machine Learning

Alireza Fallah

        Master of Science in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, June 2019.

Preprints

• Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms*

       Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman Ozdaglar

       Preprint, 2022.

• Optimal Adaptive Testing for Epidemic Control: Combining Molecular and Serology Tests*

       Daron Acemoglu, Alireza Fallah, Andrea Giometto, Daniel Huttenlocher, Asuman Ozdaglar, Sarath Pattathil

       Preprint, 2021.

• Entropic Compressibility of Lévy Processes*   

      Julien Fageot, Alireza Fallah, Thibaut Horel

       Preprint, 2020.

• Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks*

Alireza Fallah, Mert Gürbüzbalaban, Asuman Ozdaglar, Umut Simsekli, Lingjiong Zhu

       Preprint, 2019.

Conference Papers

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

Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar

      Advances in Neural Information Processing Systems (NeurIPS), 2021.

• On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning

Alireza Fallah, Kristian Georgiev, Aryan Mokhtari, Asuman Ozdaglar

      Advances in Neural Information Processing Systems (NeurIPS), 2021.

• Private Adaptive Gradient Methods for Convex Optimization*

       Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar.

       International Conference in Machine Learning (ICML), 2021.

• A Wasserstein Minimax Framework for Mixed Linear Regression* 

       Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar.

       International Conference in Machine Learning (ICML), 2021.

• Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach 

Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar

      Advances in Neural Information Processing Systems (NeurIPS), 2020.

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

Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar

       International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

• An Optimal Multistage Stochastic Gradient Method for Minimax Problems*

Alireza Fallah,  Asuman Ozdaglar, Sarath Pattathil

       IEEE Conference on Decision and Control (CDC), 2020.

• A Universally Optimal Multistage Accelerated Stochastic Gradient Method*

Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman Ozdaglar

Advances in Neural Information Processing Systems (NeurIPS), 2019.

Journal Publications

• Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions*

Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman Ozdaglar

      SIAM Journal on Optimization (SIOPT), Volume 30, Issue 1, pages 717-751, 2020.

• Multidimensional Lévy White Noise in Weighted Besov Spaces*

Julien Fageot, Alireza Fallah, Michael Unser

Stochastic Processes and their Applications, Volume 127, Issue 5, 2017.

• Sampling and Distortion Tradeoffs for Indirect Source Retrieval

Elahe Mohammadi, Alireza Fallah, Farokh Marvasti

IEEE Transactions on Information Theory, vol. 63, no. 11, pp. 6833-6848, 2017.

Also, this paper presented partially at 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

*: Names arranged in alphabetic order.