3 papers
cs.LG2025
Model Fusion via Neuron Transplantation
Muhammed Ãz, Nicholas Kiefer, Charlotte Debus +3
Ensemble learning is a widespread technique to improve the prediction performance of neural networks. However, it comes at the price of increased memory and inference time. In this…
cs.LG2024
A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting
Nicholas Kiefer, Arvid Weyrauch, Muhammed Ãz +3
The current landscape in time-series forecasting is dominated by Transformer-based models. Their high parameter count and corresponding demand in computational resources pose a cha…
cs.LG2024
AB-Training: A Communication-Efficient Approach for Distributed Low-Rank Learning
Daniel Coquelin, Katherina Flügel, Marie Weiel +5
Communication bottlenecks severely hinder the scalability of distributed neural network training, particularly in high-performance computing (HPC) environments. We introduce AB-tra…