Andrei Semenov

Gradient-Normalized Smoothness for Optimization with Approximate Hessians

arXiv 2025

Apertus: Democratizing Open and Compliant LLMs for Global Language Environments

arXiv 2025

Benchmarking Optimizers for Large Language Model Pretraining

arXiv 2025

Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed

arXiv 2024

Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning

arXiv 2024

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning

arXiv 2024

Aleksandr Beznosikov

Martin Jaggi

Alexander Gasnikov

Matteo Pagliardini

Alejandro Hernández Cano

Alexander Hägele

Alexander Hoyle

Alexander Pichugin

Alexander Sternfeld

Allen Hao Huang