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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

Yura Malitsky

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#machine learning Apr 2025

Towards Weaker Variance Assumptions for Stochastic Optimization

A classical assumption for analyzing stochastic gradient algorithms where the squared norm of the stochastic subgradient is allowed to grow as fast as the squared norm of the optimization variable is revisited.

Ahmet Alacaoglu, Yura Malitsky, Stephen J. Wright · 21 citations · ⚡3
Preprint Aug 2026

Mirror descent algorithms with logarithmic barriers

This work derives convergence guarantees for mirror descent and proximal mirror descent algorithms when a logarithmic barrier is used as a distance-generating function and shows that, in a specific setting, both methods enjoy an O(\log k / k) rate, which is also tight.

A. Marchi, Yura Malitsky, Adrien B. Taylor · 0 citations

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