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A Graph Federated Architecture with Privacy Preserving Learning


Apr 26, 2021
Elsa Rizk, Ali H. Sayed


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Competing Adaptive Networks


Mar 29, 2021
Stefan Vlaski, Ali H. Sayed


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Decision-Making Algorithms for Learning and Adaptation with Application to COVID-19 Data


Dec 14, 2020
Stefano Marano, Ali H. Sayed


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Federated Learning under Importance Sampling


Dec 14, 2020
Elsa Rizk, Stefan Vlaski, Ali H. Sayed


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Second-Order Guarantees in Federated Learning


Dec 02, 2020
Stefan Vlaski, Elsa Rizk, Ali H. Sayed


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Optimal Importance Sampling for Federated Learning


Oct 26, 2020
Elsa Rizk, Stefan Vlaski, Ali H. Sayed


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Network Classifiers Based on Social Learning


Oct 23, 2020
Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, Ali H. Sayed

* submitted for publication 

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Graph-Homomorphic Perturbations for Private Decentralized Learning


Oct 23, 2020
Stefan Vlaski, Ali H. Sayed


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Dif-MAML: Decentralized Multi-Agent Meta-Learning


Oct 06, 2020
Mert Kayaalp, Stefan Vlaski, Ali H. Sayed


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A Multi-Agent Primal-Dual Strategy for Composite Optimization over Distributed Features


Jun 15, 2020
Sulaiman A. Alghunaim, Ming Yan, Ali H. Sayed

* To appear in European Signal Processing Conference (EUSIPCO) 2020 

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Logical Team Q-learning: An approach towards factored policies in cooperative MARL


Jun 05, 2020
Lucas Cassano, Ali H. Sayed


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Tracking Performance of Online Stochastic Learners


Apr 04, 2020
Stefan Vlaski, Elsa Rizk, Ali H. Sayed


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Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization


Mar 31, 2020
Stefan Vlaski, Ali H. Sayed


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Dynamic Federated Learning


Feb 20, 2020
Elsa Rizk, Stefan Vlaski, Ali H. Sayed


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Multitask learning over graphs


Jan 07, 2020
Roula Nassif, Stefan Vlaski, Cedric Richard, Jie Chen, Ali H. Sayed


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Inverse Graph Learning over Optimization Networks


Dec 18, 2019
Vincenzo Matta, Augusto Santos, Ali H. Sayed

* submitted for publication 

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Network Classifiers With Output Smoothing


Oct 30, 2019
Elsa Rizk, Roula Nassif, Ali H. Sayed


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Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization


Oct 30, 2019
Stefan Vlaski, Ali H. Sayed

* Submitted for publication 

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Regularized Diffusion Adaptation via Conjugate Smoothing


Sep 20, 2019
Stefan Vlaski, Lieven Vandenberghe, Ali H. Sayed


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ISL: Optimal Policy Learning With Optimal Exploration-Exploitation Trade-Off


Sep 13, 2019
Lucas Cassano, Ali H. Sayed


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Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization


Aug 19, 2019
Stefan Vlaski, Ali H. Sayed


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Distributed Learning in Non-Convex Environments -- Part II: Polynomial Escape from Saddle-Points


Jul 03, 2019
Stefan Vlaski, Ali H. Sayed


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Learning Erdős-Rényi Graphs under Partial Observations: Concentration or Sparsity?


Apr 05, 2019
Vincenzo Matta, Augusto Santos, Ali H. Sayed

* Submitted for publication 

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On the Performance of Exact Diffusion over Adaptive Networks


Mar 26, 2019
Kun Yuan, Sulaiman A. Alghunaim, Bicheng Ying, Ali H. Sayed

* 10 pages, 1 figure, submitted for publication 

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Decentralized Decision-Making Over Multi-Task Networks


Dec 24, 2018
Sahar Khawatmi, Abdelhak M. Zoubir, Ali H. Sayed

* 26 pages, 13 figures, Journal paper 

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Multi-Agent Fully Decentralized Off-Policy Learning with Linear Convergence Rates


Oct 17, 2018
Lucas Cassano, Kun Yuan, Ali H. Sayed

* 28 pages, 3 figures 

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Stochastic Learning under Random Reshuffling with Constant Step-sizes


Oct 09, 2018
Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed


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Learning Kolmogorov Models for Binary Random Variables


Jun 06, 2018
Hadi Ghauch, Mikael Skoglund, Hossein Shokri-Ghadikolaei, Carlo Fischione, Ali H. Sayed

* 9 pages, accecpted to ICML 2018: Workshop on Nonconvex Optimization 

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Variance-Reduced Stochastic Learning by Networked Agents under Random Reshuffling


May 29, 2018
Kun Yuan, Bicheng Ying, Jiageng Liu, Ali H. Sayed

* 23 pages, 12 figures, submitted for publication 

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Learning Under Distributed Features


May 29, 2018
Bicheng Ying, Kun Yuan, Ali H. Sayed


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