2 papers
cs.LG2026
Heterogeneous Low-Bandwidth Pre-Training of LLMs
Yazan Obeidi, Amir Sarfi, Joel Lidin +2
Pre-training large language models (LLMs) increasingly requires distributed compute, yet bandwidth constraints make it difficult to scale beyond well-provisioned datacenters-especi…
cs.LG2023
Global Layers: Non-IID Tabular Federated Learning
Yazan Obeidi
Data heterogeneity between clients remains a key challenge in Federated Learning (FL), particularly in the case of tabular data. This work presents Global Layers (GL), a novel part…