3 papers
stat.ML2024
Statistical Multicriteria Benchmarking via the GSD-Front
Christoph Jansen, Georg Schollmeyer, Julian Rodemann +2
Given the vast number of classifiers that have been (and continue to be) proposed, reliable methods for comparing them are becoming increasingly important. The desire for reliabili…
stat.ML2024
Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision
Stefan Dietrich, Julian Rodemann, Christoph Jansen
We provide a theoretical and computational investigation of the Gamma-Maximin method with soft revision, which was recently proposed as a robust criterion for pseudo-label selectio…
stat.ML2023
In all LikelihoodS: How to Reliably Select Pseudo-Labeled Data for Self-Training in Semi-Supervised Learning
Julian Rodemann, Christoph Jansen, Georg Schollmeyer +1
Self-training is a simple yet effective method within semi-supervised learning. The idea is to iteratively enhance training data by adding pseudo-labeled data. Its generalization p…