A Robust Backward Compatibility Metric for Model Retraining. - Ryuta Matsuno; Keita Sakuma (CIKM, 2023)

Quantitative Decomposition of Prediction Errors Revealing Multi-Cause Impacts: An Insightful Framework for MLOps. - Keita Sakuma; Ryuta Matsuno; Yoshio Kameda (CIKM, 2023)

A Method of Identifying Causes of Prediction Errors to Accelerate MLOps. - Keita Sakuma; Ryuta Matsuno; Yoshio Kameda (DeepTest, 2023)

eAIEDF: Extended AI Error Diagnosis Flowchart for Automatically Identifying Misprediction Causes in Production Models. - Keita Sakuma; Ryuta Matsuno; Yoshio Kameda (ICSE Companion, 2024)

Interactive Visualization of Ensemble Decision Trees Based on the Relations Among Weak Learners. - Miyu Kashiyama; Masakazu Hirokawa; Ryuta Matsuno; Keita Sakuma; Takayuki Itoh (IV, 2024)

Model Accuracy-Oriented Data Sets Visualization for Understanding Temporal Changes in Data. - Ryuta Matsuno; Keita Sakuma; Masakazu Hirokawa (IV, 2024)

Improved Impossible Tuning and Lipschitz-Adaptive Universal Online Learning with Gradient Variations. - Kei Takemura; Ryuta Matsuno; Keita Sakuma (CoRR, 2025)