Welcome to the Machine Learning Lab at the University of Freiburg!
Machine learning (ML) is the key technology of our time. However, so far, its success crucially relies on human machine learning experts to perform manual tasks, thus limiting its potential impact. To overcome this issue, here at the ML Lab, we focus on the progressive automation of machine learning (AutoML) in order to democratize access to ML by making state-of-the-art ML solutions accessible for everyone, in world-leading open source systems. Framed differently, and from a technical point of view, our lab develops AI that builds AI.
Particular technical fields of interest for us include meta-learning, neural architecture search, efficient hyperparameter optimization, deep learning for tabular data, multi-objective optimization, proper benchmarking, and AutoRL. We also apply AutoML to improve practical deep learning for several applications of high societal importance, such as RNA folding and design, EEG decoding, and data from the medical sector in general.
We co-organize the MOOC on AutoML at KI Campus and the lab's prof, Frank Hutter, is general chair of the AutoML conference and also the head of the ELLIS unit Freiburg, one of the 17 founding units of the European Laboratory for Learning and Intelligent Systems (ELLIS).
On this university website, we provide information about our publications, teaching, open student projects, and how to get in touch to start working with us. We discuss AutoML in detail on our project webpage AutoML.org, including our open-source libraries, our blog, upcoming and past events, and our MOOC.
|News||(We just restarted this news section; older news to be filled in soon.)|
|23.12.2022||We are organizing the next AutoML Conference! All important dates and details can be found through automl.cc|
|05.12.2022||TabPFN won the best paper award at the NeurIPS'22 TRL Workshop.|
|14.11.2022||We'll present 17 papers at NeurIPS 2022: 2 at the main conference, 2 at the datasets and benchmark track, and 13 at workshops!|
|10.10.2022||We're organizing the AutoML Fall School 2022 here in Freiburg|
|01.09.2022||Herilalaina Rakotoarison joins the Lab as Postdoc.|
|13.07.2022||Our GECCO’22 paper Theory-Inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration|
won the best paper award on the GECH track
|15.03.2022||Frank has been awarded an ERC Consolidator Grant for the topic Deep Learning 2.0!|