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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Li-Sha Chen

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Preprint Jul 2026

Improved Convergence Rates for Stochastic Multi-Gradient Descent which Close the Gap: A Proof by AI

A new convergence rate for SMG in terms of the squared Pareto-stationarity (PS) measure is established, to exploit the Lipschitz continuity of the PS measure, defined by the norm of the multi-gradient descent algorithm (MGDA) direction, rather than the $(1/2)-H\"older continuity of the MGDA direction.

Li-Sha Chen · 0 citations
Preprint Jul 2026

Improved Convergence Rate for Stochastic Multi-Gradient Descent: A Proof Discovered with AI

For smooth nonconvex stochastic multi-objective problems, stochastic multi-gradient descent (SMG) computes an approximate steepest common descent direction of the objectives from stochastic gradients. With unbiased, variance-bounded stochastic gradients, this note establishes a new convergence rate for SMG in terms of...

Lisha Chen · 0 citations

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