Skip to content

Author

B. Leimkuhler

We have 2 of 12 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint Sep 2026

Low-Rank Friction for Memory-Efficient Transformer Pretraining

iKFAD is a recently proposed optimiser that replaces adaptive learning rates with adaptive friction in the momentum dynamics, yet performs as well as Adam. Its limitation is that the full friction tensor $\xi\in\mathbb{R}^{m\times n}$ carries the same $\mathcal{O}(mn)$ memory overhead per layer as Adam's second-moment...

Rajit Rajpal, B. Leimkuhler · 0 citations
Open access Aug 2026

Unbiased kinetic Langevin Monte Carlo with inexact gradients

Theoretical analysis demonstrates that the proposed estimator is unbiased, attains finite variance, and satisfies a central limit theorem, and the results demonstrate that in large-scale applications, the unbiased algorithm can be 2–3 orders of magnitude more efficient than the “gold-standard” randomized Hamiltonian Mo...

N. K. Chada, B. Leimkuhler, Daniel Paulin et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.