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pro vyhledávání: '"Ishibashi, Hideaki"'
In this study, we develop a method for multi-task manifold learning. The method aims to improve the performance of manifold learning for multiple tasks, particularly when each task has a small number of samples. Furthermore, the method also aims to g
Externí odkaz:
http://arxiv.org/abs/2111.11655
Autor:
Ishibashi, Hideaki, Akaho, Shotaro
Publikováno v:
Neural Computation, 34, 1189-1219, 2022
This paper proposes an extension of principal component analysis for Gaussian process (GP) posteriors, denoted by GP-PCA. Since GP-PCA estimates a low-dimensional space of GP posteriors, it can be used for meta-learning, which is a framework for impr
Externí odkaz:
http://arxiv.org/abs/2107.07115
Autor:
Ishibashi, Hideaki, Hino, Hideitsu
Active learning is a framework for supervised learning to improve the predictive performance by adaptively annotating a small number of samples. To realize efficient active learning, both an acquisition function that determines the next datum and a s
Externí odkaz:
http://arxiv.org/abs/2104.01836
Visual analytics (VA) is a visually assisted exploratory analysis approach in which knowledge discovery is executed interactively between the user and system in a human-centered manner. The purpose of this study is to develop a method for the VA of s
Externí odkaz:
http://arxiv.org/abs/2104.09231
Autor:
Ishibashi, Hideaki, Hino, Hideitsu
Active learning is a framework in which the learning machine can select the samples to be used for training. This technique is promising, particularly when the cost of data acquisition and labeling is high. In active learning, determining the timing
Externí odkaz:
http://arxiv.org/abs/2005.07402
Autor:
Sakamoto, Kotaro, Ishibashi, Hideaki, Sato, Rei, Shirakawa, Shinichi, Akimoto, Youhei, Hino, Hideitsu
Publikováno v:
In Neural Networks September 2023 166:446-458
Publikováno v:
In Neurocomputing 7 February 2022 473:138-157
Publikováno v:
In Decision Support Systems January 2022 152
Akademický článek
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Autor:
Maruya, Kohei, Fujita, Hiroaki, Arai, Tomoyuki, Asahi, Ryoma, Morita, Yasuhiro, Ishibashi, Hideaki
Publikováno v:
In Osteoporosis and Sarcopenia March 2019 5(1):23-26