Tyler Farghly

Tyler Farghly

Learning theory, Optimisation, Monte Carlo methods

I am a DPhil student at the University of Oxford supervised by Patrick Rebeschini and Arnaud Doucet. Before this, I studied Mathematics at Imperial College London. I’m interested in optimisation and theoretical foundations for machine learning. Most recently, I have been interested in measures of generalisation, the use of noise for regularisation and the relationship between optimisation and sampling.



  • T. Farghly , P. Rebeschini , Time-independent Generalization Bounds for SGLD in Non-convex Settings, in Advances in Neural Information Processing Systems 34, 2021.