no code implementations • 25 Apr 2024 • Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik, Samir Garibov, Edward Bergman, Frank Hutter
In this work, we propose FT-PFN, a novel surrogate for Freeze-thaw style BO.
1 code implementation • ICLR 2022 • Herilalaina Rakotoarison, Louisot Milijaona, Andry Rasoanaivo, Michele Sebag, Marc Schoenauer
This paper tackles the AutoML problem, aimed to automatically select an ML algorithm and its hyper-parameter configuration most appropriate to the dataset at hand.
no code implementations • 8 Oct 2020 • Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong, Baptiste Roziere, Jeremy Rapin, Olivier Teytaud, Antoine Moreau, Carola Doerr
We demonstrate the advantages of such a broad collection by deriving from it Automated Black Box Optimizer (ABBO), a general-purpose algorithm selection wizard.
no code implementations • 24 Jun 2020 • Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag
On both tasks, Dida learns meta-features supporting the characterization of a (labelled) dataset.
2 code implementations • 1 Jun 2019 • Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag
The AutoML task consists of selecting the proper algorithm in a machine learning portfolio, and its hyperparameter values, in order to deliver the best performance on the dataset at hand.