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Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach


Jun 10, 2021
Qiujiang Jin, Aryan Mokhtari


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Exploiting Shared Representations for Personalized Federated Learning


Feb 14, 2021
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai


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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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Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity


Dec 28, 2020
Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani


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Why Does MAML Outperform ERM? An Optimization Perspective


Oct 27, 2020
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai


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Submodular Meta-Learning


Jul 11, 2020
Arman Adibi, Aryan Mokhtari, Hamed Hassani


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Federated Learning with Compression: Unified Analysis and Sharp Guarantees


Jul 02, 2020
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi

* 52 pages 

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Safe Learning under Uncertain Objectives and Constraints


Jun 23, 2020
Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani

* 42 pages, 2 figures 

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Hybrid Model for Anomaly Detection on Call Detail Records by Time Series Forecasting


Jun 07, 2020
Aryan Mokhtari, Leyla Sadighi, Behnam Bahrak, Mojtaba Eshghie


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Non-asymptotic Superlinear Convergence of Standard Quasi-Newton Methods


Mar 30, 2020
Qiujiang Jin, Aryan Mokhtari


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Quantized Push-sum for Gossip and Decentralized Optimization over Directed Graphs


Feb 25, 2020
Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani


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Personalized Federated Learning: A Meta-Learning Approach


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


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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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Distribution-Agnostic Model-Agnostic Meta-Learning


Feb 12, 2020
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai


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A Decentralized Proximal Point-type Method for Saddle Point Problems


Oct 31, 2019
Weijie Liu, Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng

* 18 pages 

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FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization


Oct 12, 2019
Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani


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One Sample Stochastic Frank-Wolfe


Oct 10, 2019
Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi


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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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Robust and Communication-Efficient Collaborative Learning


Jul 24, 2019
Amirhossein Reisizadeh, Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani


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Proximal Point Approximations Achieving a Convergence Rate of $\mathcal{O}(1/k)$ for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods


Jun 03, 2019
Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil

* 15 pages 

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Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization


Mar 06, 2019
Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi


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Stochastic Conditional Gradient++


Feb 19, 2019
Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen

* Submitted to COLT 2019 

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A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach


Jan 24, 2019
Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil

* 31 pages, 3 figures 

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Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy


Oct 26, 2018
Majid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takáč


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Escaping Saddle Points in Constrained Optimization


Oct 09, 2018
Aryan Mokhtari, Asuman Ozdaglar, Ali Jadbabaie


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Direct Runge-Kutta Discretization Achieves Acceleration


Sep 14, 2018
Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie

* 24 pages. 4 figures 

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