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03/23/2023
Decentralized Adversarial Training over Graphs
The vulnerability of machine learning models to adversarial attacks has ...
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03/03/2023
Multi-Agent Adversarial Training Using Diffusion Learning
This work focuses on adversarial learning over graphs. We propose a gene...
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01/16/2023
Enforcing Privacy in Distributed Learning with Performance Guarantees
We study the privatization of distributed learning and optimization stra...
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10/26/2022
Local Graph-homomorphic Processing for Privatized Distributed Systems
We study the generation of dependent random numbers in a distributed fas...
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03/14/2022
Privatized Graph Federated Learning
Federated learning is a semi-distributed algorithm, where a server commu...
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04/26/2021
A Graph Federated Architecture with Privacy Preserving Learning
Federated learning involves a central processor that works with multiple...
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12/14/2020
Federated Learning under Importance Sampling
Federated learning encapsulates distributed learning strategies that are...
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12/02/2020
Second-Order Guarantees in Federated Learning
Federated learning is a useful framework for centralized learning from d...
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10/26/2020
Optimal Importance Sampling for Federated Learning
Federated learning involves a mixture of centralized and decentralized p...
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04/04/2020
Tracking Performance of Online Stochastic Learners
The utilization of online stochastic algorithms is popular in large-scal...
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02/20/2020
Dynamic Federated Learning
Federated learning has emerged as an umbrella term for centralized coord...
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10/30/2019
