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The Representation Learning Lab (RELEA) led by Prof. Dr. Josif Grabocka was founded in 01.12.2019 and focuses on exploring Deep Learning representations to tackle diverse Machine Learning tasks arising in practical data-driven application domains. In particular, the lab is focused on Neural Architecture Search, Hyper-Parameter Optimization, as well as designing end-to-end architectures for sequential data (time-series) and Recommender System prediction tasks.

 

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Recent News

Article icon.   12.02.2021   Prof. Grabocka gave an invited talk titled “Deep Learning for Tabular Datasets” at the Freiburg Center for Data Analysis and Modeling’s seminar on "Data Analysis and Modeling".

Article icon.   12.01.2021   Our newest paper Few-Shot Bayesian Optimization with Deep Kernel Surrogates is accepted in the Ninth International Conference on Learning Representations (ICLR 2021).

Article icon.   15.11.2020   Our paper Dataset2Vec: Learning Dataset Meta-Features is accepted in the Journal of Data Mining and Knowledge Discovery.

Article icon.   30.07.2020   Prof. Grabocka receives a research grant of 300.000 Euro by the Eva Mayr-Stihl Stiftung.

Article icon.   01.07.2020   Michael Ruchte and Arlind Kadra join RELEA as Doctoral Researchers.

Article icon.   01.07.2020   Prof. Dr. Grabocka becomes a member of the Cluster of Excellence BrainLinks-BrainTools on interdisciplinary neurotechnological research funded by the MWK BW.

Article icon.   01.12.2019   Josif Grabocka is appointed as an Assistant Professor of Representation Learning at the University of Freiburg, marking the beginning of the RELEA lab.