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Shota Saito
Shota Saito
Verified email at gunma-u.ac.jp - Homepage
Title
Cited by
Cited by
Year
Probability distribution on full rooted trees
Y Nakahara, S Saito, A Kamatsuka, T Matsushima
Entropy 24 (3), 328, 2022
232022
Meta-tree random forest: Probabilistic data-generative model and Bayes optimal prediction
N Dobashi, S Saito, Y Nakahara, T Matsushima
Entropy 23 (6), 768, 2021
182021
Non-asymptotic fundamental limits of guessing subject to distortion
S Saito, T Matsushima
2019 IEEE International Symposium on Information Theory (ISIT), 652-656, 2019
72019
Non-asymptotic bounds of cumulant generating function of codeword lengths in variable-length lossy compression
S Saito, T Matsushima
IEEE Transactions on Information Theory 69 (4), 2113-2119, 2022
62022
An efficient Bayes coding algorithm for the non-stationary source in which context tree model varies from interval to interval
K Shimada, S Saito, T Matsushima
2021 IEEE Information Theory Workshop (ITW), 1-6, 2021
62021
Evaluation of error probability of classification based on the analysis of the Bayes code
S Saito, T Matsushima
2020 IEEE International Symposium on Information Theory (ISIT), 2510-2514, 2020
62020
Fundamental limit and pointwise asymptotics of the Bayes code for Markov sources
S Saito, N Miya, T Matsushima
2015 IEEE International Symposium on Information Theory (ISIT), 1986-1990, 2015
62015
Evaluation of the minimum overflow threshold of Bayes codes for a Markov source
S Saito, N Miya, T Matsushima
2014 International Symposium on Information Theory and its Applications, 211-215, 2014
62014
Probability distribution on rooted trees
Y Nakahara, S Saito, A Kamatsuka, T Matsushima
2022 IEEE International Symposium on Information Theory (ISIT), 174-179, 2022
52022
Threshold of overflow probability in terms of smooth max-entropy for variable-length compression allowing errors
S Saito, T Matsushima
2016 International Symposium on Information Theory and Its Applications …, 2016
52016
Hyperparameter Learning of Bayesian Context Tree Models
Y Nakahara, S Saito, K Shimada, T Matsushima
2023 IEEE International Symposium on Information Theory (ISIT), 537-542, 2023
42023
Evaluation of error probability of classification based on the analysis of the Bayes code: Extension and example
S Saito, T Matsushima
2021 IEEE International Symposium on Information Theory (ISIT), 1445-1450, 2021
42021
Cumulant generating function of codeword lengths in variable-length lossy compression allowing positive excess distortion probability
S Saito, T Matsushima
2018 IEEE International Symposium on Information Theory (ISIT), 881-885, 2018
42018
Spatially “mt. fuji” coupled ldpc codes
Y Nakahara, S Saito, T Matsushima
IEICE Transactions on Fundamentals of Electronics, Communications and …, 2017
42017
Variable-length lossy compression allowing positive overflow and excess distortion probabilities
S Saito, H Yagi, T Matsushima
2017 IEEE International Symposium on Information Theory (ISIT), 1568-1572, 2017
42017
Threshold of overflow probability using smooth max-entropy in lossless fixed-to-variable length source coding for general sources
S Saito, T Matsushima
IEICE Transactions on Fundamentals of Electronics, Communications and …, 2016
42016
Evaluation of overflow probability of Bayes code in moderate deviation regime
S Saito, T Matsushima
2016 International Symposium on Information Theory and Its Applications …, 2016
42016
Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and Interpretability
Y Nakahara, S Saito, N Ichijo, K Kazama, T Matsushima
The 28th International Conference on Artificial Intelligence and Statistics, 2025
32025
On meta-bound for lower bounds of Bayes risk
S Saito
2022 IEEE International Symposium on Information Theory (ISIT), 3162-3167, 2022
32022
New results on variable-length lossy compression allowing positive overflow and excess distortion probabilities
S Saito, H Yagi, T Matsushima
2018 International Symposium on Information Theory and Its Applications …, 2018
32018
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Articles 1–20