Christoph H. Lampert

collaborators

3 papers

cs.LG2026

Towards Robust Scaling Laws for Optimizers

Alexandra Volkova, Mher Safaryan, Christoph H. Lampert +1

The quality of Large Language Model (LLM) pretraining depends on multiple factors, including the compute budget and the choice of optimization algorithm. Empirical scaling laws are…

cs.CR2025

Differentially Private Federated $k$ -Means Clustering with Server-Side Data

Jonathan Scott, Christoph H. Lampert, David Saulpic

Clustering is a cornerstone of data analysis that is particularly suited to identifying coherent subgroups or substructures in unlabeled data, as are generated continuously in larg…

cs.LG2025

PeFLL: Personalized Federated Learning by Learning to Learn

Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert

We present PeFLL, a new personalized federated learning algorithm that improves over the state-of-the-art in three aspects: 1) it produces more accurate models, especially in the l…

Towards Robust Scaling Laws for Optimizers

Differentially Private Federated k-Means Clustering with Server-Side Data

PeFLL: Personalized Federated Learning by Learning to Learn

Differentially Private Federated $k$ -Means Clustering with Server-Side Data