研究内容

AI・機械学習

Bayesian Context Tree Model

  • Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima, "Probability Distribution on Rooted Trees: Generalization from Full Trees," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2026, Volume E109.A, Issue 3, Pages 524-537. Link
  • Yuta Nakahara, Shota Saito, Naoki Ichijo, Koki Kazama, Toshiyasu Matsushima, "Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and Interpretability,"  Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 258:1045-1053, 2025. Link (難関国際会議 AISTATS に採録
  • Y. Nakahara, S. Saito, K. Shimada and T. Matsushima, "Hyperparameter Learning of Bayesian Context Tree Models," 2023 IEEE International Symposium on Information Theory (ISIT), Taipei, Taiwan, 2023, pp. 537-542, doi: 10.1109/ISIT54713.2023.10206456.   Link
  • Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima. 2022. "Probability Distribution on Full Rooted Trees" Entropy, 24, no. 3: 328. https://doi.org/10.3390/e24030328 Link
  • Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima, "Probability Distribution on Rooted Trees," 2022 IEEE International Symposium on Information Theory (ISIT), Espoo, Finland, 2022, pp. 174-179, doi: 10.1109/ISIT50566.2022.9834481. Link
  • Nao Dobashi, Shota Saito, Yuta Nakahara, and Toshiyasu Matsushima. 2021. "Meta-Tree Random Forest: Probabilistic Data-Generative Model and Bayes Optimal Prediction" Entropy, 23, no. 6: 768. https://doi.org/10.3390/e23060768 Link


潜在クラスモデル

  • Ishiwatari, T., Saito, S., Nakahara, Y. et al. Bayes optimal estimation and its approximation algorithm for difference with and without treatment under IRSLC model. Int J Data Sci Anal (2023). https://doi.org/10.1007/s41060-023-00468-8 Link
  • Murayama, H., Saito, S., Iikubo, Y. et al. Cluster’s Number Free Bayes Prediction of General Framework on Mixture of Regression Models. J Stat Theory Appl 20, 425–449 (2021). https://doi.org/10.1007/s44199-021-00001-5 Link


ベイズリスクの下界

  • Shota Saito, "Meta-Bound on Lower Bounds of Bayes Risk in Parameter Estimation," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2024, Volume E107.A, Issue 3, Pages 503-509 Link
  • S. Saito, "On Meta-Bound for Lower Bounds of Bayes Risk," 2022 IEEE International Symposium on Information Theory (ISIT), Espoo, Finland, 2022, pp. 3162-3167, doi: 10.1109/ISIT50566.2022.9834810.   Link


ベイズ符号の符号語長解析の応用

  • Shota Saito and Toshiyasu Matsushima, "Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code: Extension and Example," 2021 IEEE International Symposium on Information Theory (ISIT), Melbourne, Australia, 2021, pp. 1445-1450, doi: 10.1109/ISIT45174.2021.9517718. Link
  • Shota Saito and Toshiyasu Matsushima, "Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code," 2020 IEEE International Symposium on Information Theory (ISIT), Los Angeles, CA, USA, 2020, pp. 2510-2514, doi: 10.1109/ISIT44484.2020.9173981. Link