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12/22/2022
Nonlinear consensus+innovations under correlated heavy-tailed noises: Mean square convergence rate and asymptotics
We consider distributed recursive estimation of consensus+innovations ty...
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11/02/2022
Large deviations rates for stochastic gradient descent with strongly convex functions
Recent works have shown that high probability metrics with stochastic gr...
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09/22/2022
One-Shot Federated Learning for Model Clustering and Learning in Heterogeneous Environments
We propose a communication efficient approach for federated learning in ...
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08/10/2022
Inaccuracy rates for distributed inference over random networks with applications to social learning
This paper studies probabilistic rates of convergence for consensus+inno...
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05/23/2022
Dynamic Split Computing for Efficient Deep Edge Intelligence
Deploying deep neural networks (DNNs) on IoT and mobile devices is a cha...
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04/06/2022
Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noise
We introduce a general framework for nonlinear stochastic gradient desce...
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02/01/2022
Gradient Based Clustering
We propose a general approach for distance based clustering, using the g...
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02/01/2022
Personalized Federated Learning via Convex Clustering
We propose a parametric family of algorithms for personalized federated ...
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02/17/2021
Deep Learning Anomaly Detection for Cellular IoT with Applications in Smart Logistics
The number of connected Internet of Things (IoT) devices within cyber-ph...
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12/18/2019
Primal-dual optimization methods for large-scale and distributed data analytics
The augmented Lagrangian method (ALM) is a classical optimization tool t...
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12/25/2017
