3 papers
cs.LG2026
CacheMuon: Using Temporal Preconditioning To Approximate Polar Factor
Bishnu Dev, Sushil Bohara, Martin TakÃ¡Ä +1
Muon is an optimizer that computes updates using the polar factor of the momentum matrix and has shown strong empirical performance across a range of training settings. A key compo…
stat.ML2025
Geometric Convergence Analysis of Variational Inference via Bregman Divergences
Sushil Bohara, Amedeo Roberto Esposito
Variational Inference (VI) provides a scalable framework for Bayesian inference by optimizing the Evidence Lower Bound (ELBO), but convergence analysis remains challenging due to t…
math.OC2025
Loss-Transformation Invariance in the Damped Newton Method
Alexander Shestakov, Sushil Bohara, Samuel Horváth +2
The Newton method is a powerful optimization algorithm, valued for its rapid local convergence and elegant geometric properties. However, its theoretical guarantees are usually lim…