Evolution of Efficient and Robust AutoML Systems

Evolution of Efficient and Robust AutoML Systems

Explore the evolution of efficient and robust AutoML systems in this 32-minute conference talk. Delve into the technical methods behind recent advancements, starting with a brief recap of early systems like Auto-WEKA and Auto-sklearn. Examine the next generation of AutoML, including Auto-learn 2.0 and Auto-PyTorch, focusing on components that significantly improve efficiency. Learn about practical considerations, multi-fidelity optimization, portfolio construction, and automated policy selection. Discover how these approaches outperform Auto-sklearn 1.0 and gain insights into regularization techniques for state-of-the-art deep learning on tabular data.