no code implementations • 26 Dec 2022 • Kazuhiko Shinoda, Takahiro Hoshino
This chapter develops the general framework for estimation and inference on CEFR, which allows the use of flexible machine learning for infinite-dimensional nuisance parameters.
no code implementations • 11 Sep 2021 • Kazuhiko Shinoda, Takahiro Hoshino
However, model selection and hyperparameter tuning for the direct least squares estimator can be unstable in practice since it is defined as a solution to the minimax problem.
no code implementations • 29 Jan 2020 • Kazuhiko Shinoda, Hirotaka Kaji, Masashi Sugiyama
Positive-confidence (Pconf) classification [Ishida et al., 2018] is a promising weakly-supervised learning method which trains a binary classifier only from positive data equipped with confidence.