Regularization-Based Methods for Ordinal Quantification

1 code implementation • 13 Oct 2023 • Mirko Bunse, Alejandro Moreo, Fabrizio Sebastiani, Martin Senz

Quantification, i. e., the task of training predictors of the class prevalence values in sets of unlabeled data items, has received increased attention in recent years.

Noisy Labels for Weakly Supervised Gamma Hadron Classification

no code implementations • 30 Aug 2021 • Lukas Pfahler, Mirko Bunse, Katharina Morik

Gamma hadron classification, a central machine learning task in gamma ray astronomy, is conventionally tackled with supervised learning.

Astronomy Classification

Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots

no code implementations • 29 Oct 2020 • Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras, Mario Morvan, Billy Edwards, Kai Hou Yip, Giovanna Tinetti, Subhajit Sarkar, James M. Dawson, Vadim Borisov, Gjergji Kasneci, Matej Petkovic, Tomaz Stepisnik, Tarek Al-Ubaidi, Rachel Louise Bailey, Michael Granitzer, Sahib Julka, Roman Kern, Patrick Ofner, Stefan Wagner, Lukas Heppe, Mirko Bunse, Katharina Morik

For instance, the most prolific method for detecting exoplanets and inferring several of their characteristics, transit photometry, is very sensitive to the presence of stellar spots.

BIG-bench Machine Learning