Adaptation and Learning – Page 4 – ASL – Adaptive Systems Laboratory

Decentralized proximal gradient algorithms with linear convergence rates

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Decision learning and adaptation over multi-task networks

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Multi-agent fully decentralized value function learning with linear convergence rates,

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Distributed learning in non-convex environments – Part II: Polynomial escape from saddle points

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Distributed learning in non-convex environments – Part I: Agreement at a linear rate

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Graph learning under partial observability

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Second-order guarantees in centralized, federated and decentralized nonconvex optimization

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Convex combination of diffusion strategies over networks

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A proximal diffusion strategy for multi-agent optimization with sparse affine constraints

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Diffusion LMS with communication delays: Stability and performance analysis

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