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Diego Granziol

3 accepted papers

2025

Compute-Optimal LLMs Provably Generalize Better with Scale

ICLR 2025poster

Why do larger language models generalize better? To explore this question, we develop generalization bounds on the pretraining objective of large language models (LLMs) in the compute-optimal regime, as described by the Chinchilla scaling laws. We introduce a novel, fully empirical Freedman-type mar…

Cited by 0SourcePDFScholar
2018

Fast Information-theoretic Bayesian Optimisation

ICML 2018oral

Information-theoretic Bayesian optimisation techniques have demonstrated state-of-the-art performance in tackling important global optimisation problems. However, current information-theoretic approaches require many approximations in implementation, introduce often-prohibitive computational overhea…