2 papers
stat.ML2025
Data-driven Projection Generation for Efficiently Solving Heterogeneous Quadratic Programming Problems
Tomoharu Iwata, Futoshi Futami
We propose a data-driven framework for efficiently solving quadratic programming (QP) problems by reducing the number of variables in high-dimensional QPs using instance-specific p…
cs.LG2023
Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers
Yuya Yoshikawa, Tomoharu Iwata
The quality of explanations for the predictions made by complex machine learning predictors is often measured using insertion and deletion metrics, which assess the faithfulness of…