年別の研究成果
年別の研究成果
フィンガープリント
Yuta Nakaharaが活動している研究トピックを掘り下げます。このトピックラベルは、この研究者の研究成果に基づきます。これらがまとまってユニークなフィンガープリントを構成します。
- 9 類似のプロファイル
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Analysis of decoding error probability of spatially "Mt. Fuji" coupled LDPC codes inwaterfall region of the BEC
NAKAHARA, Y. & Matsushima, T., 2020 12, In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. E103A, 12, p. 1337-1346 10 p.研究成果: Article › 査読
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A stochastic model of block segmentation based on the quadtree and the bayes code for it
Nakahara, Y. & Matsushima, T., 2020 3, Proceedings - DCC 2020: Data Compression Conference. Bilgin, A., Marcellin, M. W., Serra-Sagrista, J. & Storer, J. A. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 293-302 10 p. 9105877. (Data Compression Conference Proceedings; vol. 2020-March).研究成果: Conference contribution
1 被引用数 (Scopus) -
Autoregressive Image Generative Models with Normal and t-distributed Noise and the Bayes Codes for Them
Nakahara, Y. & Matsushima, T., 2020 10 24, Proceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020. Institute of Electrical and Electronics Engineers Inc., p. 81-85 5 p. 9366177. (Proceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020).研究成果: Conference contribution
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Bayes Code for 2-dimensional auto-regressive Hidden Markov model and its application to lossless image compression
Nakahara, Y. & Matsushima, T., 2020, International Workshop on Advanced Imaging Technology, IWAIT 2020. Lau, P. Y. & Shobri, M. (eds.). SPIE, 115151T. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11515).研究成果: Conference contribution
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Theoretical Analysis of the Advantage of Deepening Neural Networks
Esaki, Y., Nakahara, Y. & Matsushima, T., 2020 12, Proceedings - 19th IEEE International Conference on Machine Learning and Applications, ICMLA 2020. Wani, M. A., Luo, F., Li, X., Dou, D. & Bonchi, F. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 479-484 6 p. 9356275. (Proceedings - 19th IEEE International Conference on Machine Learning and Applications, ICMLA 2020).研究成果: Conference contribution