Author Archives: Lucas Zimmer

Auto-PyTorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL

By , ,

Auto-PyTorch is a framework for automated deep learning (AutoDL) that uses BOHB as a backend to optimize the full deep learning pipeline, including data preprocessing, network training techniques and regularization methods. Auto-PyTorch is the successor of AutoNet which was one of the first frameworks to perform this joint optimization. (more…)

Read More

Best Practices for Scientific Research on Neural Architecture Search

By ,

Based on our NAS literature list

Neural architecture search (NAS) is currently one of the hottest topics in automated machine learning (see AutoML book), with a seemingly exponential increase in the number of papers written on the subject, see the figure above. While many NAS methods are fascinating (please see our survey article for an overview of the main trends and a taxonomy of NAS methods), in this blog post we will not focus on these methods themselves, but on how to evaluate them scientifically. (more…)

Read More