Eindhoven University of Technology, Netherlands
Google Scholar: https://scholar.google.co.uk/citations?user=HhDsD9UAAAAJ&hl=en
Title: Learning how to learn with OpenML
Machine learning aims to perform tasks better based on data and automatically gained experience. Ironically, doing it well often requires a lot of tacit human experience and starting from scratch. What if we could automatically collect experience on how to learn across a wide range of tasks, on a global scale, and spanning many lifetimes? OpenML is an open-source platform for doing exactly this. It allows anyone (and anything) to share machine learning datasets, models, and reproducible experiments. It is integrated into popular machine learning tools to allow easy sharing of models and experiments. It organizes all of this online with rich metadata, and enables anyone to reuse and build on them in novel and unexpected ways. This fosters a budding ecosystem of automated processes that can learn from all shared information on how to build the best machine learning models faster and better over time. We welcome all of you to become a part of it.
Joaquin Vanschoren is an assistant professor at the Eindhoven University of Technology (TU/e). His research focuses on the automation of machine learning (AutoML) and Meta-Learning. He co-authored and co-edited the book 'Automatic Machine: Methods, Systems, Challenges'', published over 100 articles on these topics, and received an Amazon Research Award, Azure Research Award, and the Dutch Data Prize. He founded and leads OpenML.org, an open science platform for machine learning, and is a founding member of the European AI associations ELLIS and CLAIRE. He has been tutorial speaker at NeurIPS and AAAI, and has given more than 20 invited talks. He is datasets and benchmarks chair at NeurIPS 2021 and co-organized the AutoML and Meta-Learning workshop series at NeurIPS and ICML from 2013 to 2021.