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09/04/2023
Smoothing ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties
This paper investigates quantile regression in the presence of non-conve...
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08/31/2023
Moreau Envelope ADMM for Decentralized Weakly Convex Optimization
This paper proposes a proximal variant of the alternating direction meth...
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08/31/2023
Robust Networked Federated Learning for Localization
This paper addresses the problem of localization, which is inherently no...
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06/24/2023
Zero-Concentrated Private Distributed Learning for Nonsmooth Objective Functions
This paper develops a fully distributed differentially-private learning ...
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06/10/2023
Personalized Graph Federated Learning with Differential Privacy
This paper presents a personalized graph federated learning (PGFL) frame...
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03/27/2023
Asynchronous Online Federated Learning with Reduced Communication Requirements
Online federated learning (FL) enables geographically distributed device...
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02/14/2023
Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs
The goal of this paper is to make a strong point for the usage of dynami...
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11/27/2021
Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression
Many assumptions in the federated learning literature present a best-cas...
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10/13/2021
Communication-Efficient Online Federated Learning Framework for Nonlinear Regression
Federated learning (FL) literature typically assumes that each client ha...
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07/06/2020
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
Algorithm selection (AS) deals with the automatic selection of an algori...
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04/20/2020
