
Competing Adaptive Networks
Adaptive networks have the capability to pursue solutions of global stoc...
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Deception in Social Learning
A common assumption in the social learning literature is that agents exc...
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Federated Learning under Importance Sampling
Federated learning encapsulates distributed learning strategies that are...
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SecondOrder Guarantees in Federated Learning
Federated learning is a useful framework for centralized learning from d...
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Optimal Importance Sampling for Federated Learning
Federated learning involves a mixture of centralized and decentralized p...
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GramianBased Adaptive Combination Policies for Diffusion Learning over Networks
This paper presents an adaptive combination strategy for distributed lea...
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Network Classifiers Based on Social Learning
This work proposes a new way of combining independently trained classifi...
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GraphHomomorphic Perturbations for Private Decentralized Learning
Decentralized algorithms for stochastic optimization and learning rely o...
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DifMAML: Decentralized MultiAgent MetaLearning
The objective of metalearning is to exploit the knowledge obtained from...
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Tracking Performance of Online Stochastic Learners
The utilization of online stochastic algorithms is popular in largescal...
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SecondOrder Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
Rapid advances in data collection and processing capabilities have allow...
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Dynamic Federated Learning
Federated learning has emerged as an umbrella term for centralized coord...
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Multitask learning over graphs
The problem of learning simultaneously several related tasks has receive...
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Linear Speedup in SaddlePoint Escape for Decentralized NonConvex Optimization
Under appropriate cooperation protocols and parameter choices, fully dec...
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Regularized Diffusion Adaptation via Conjugate Smoothing
The purpose of this work is to develop and study a distributed strategy ...
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SecondOrder Guarantees of Stochastic Gradient Descent in NonConvex Optimization
Recent years have seen increased interest in performance guarantees of g...
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Distributed Learning in NonConvex Environments – Part II: Polynomial Escape from SaddlePoints
The diffusion strategy for distributed learning from streaming data empl...
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Distributed Learning in NonConvex Environments – Part I: Agreement at a Linear Rate
Driven by the need to solve increasingly complex optimization problems i...
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Adaptation and learning over networks under subspace constraints – Part II: Performance Analysis
Part I of this paper considered optimization problems over networks wher...
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Adaptation and learning over networks under subspace constraints  Part I: Stability Analysis
This paper considers optimization problems over networks where agents ha...
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Adaptation and learning over networks under subspace constraints
This paper considers optimization problems over networks where agents ha...
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Learning over Multitask Graphs  Part II: Performance Analysis
Part I of this paper formulated a multitask optimization problem where a...
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Learning over Multitask Graphs  Part I: Stability Analysis
This paper formulates a multitask optimization problem where agents in t...
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Stochastic Learning under Random Reshuffling
In empirical risk optimization, it has been observed that stochastic gra...
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Stefan Vlaski
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