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pro vyhledávání: '"Yasuo Matsuyama"'
Autor:
Yasuo Matsuyama
Publikováno v:
IEEE Access, Vol 9, Pp 24546-24559 (2021)
This study interrelates three adjacent topics in data evaluation. The first is the establishment of a relationship between Bregman divergence and probabilistic alpha-divergence. In particular, we demonstrate that square-root-order probability normali
Externí odkaz:
https://doaj.org/article/e361b4e601c94a2c8172213cbd5a0171
Autor:
Yasuo Matsuyama
Publikováno v:
IEEE Transactions on Signal Processing. 65:3446-3461
The estimation of generative structures for sequences is becoming increasingly important for preventing such data sources from becoming a flood of disorganized information. Obtaining hidden Markov models (HMMs) has been a central method for structuri
Autor:
Yasuo Matsuyama
Publikováno v:
ISIT
We present a path starting from generalized information measures to blockchain applications. In the middle of these two endpoints, we derive the alpha-EM algorithm and the traditional log-EM algorithm simultaneously from a sole divergence. Thus, ther
Publikováno v:
Neurocomputing. 164:137-143
In this paper, we propose a method to utilize low-frequency brain signals for continuous authentication of users. During such monitoring, the users to be authenticated can work without interruption. This style of authentication is expected to complem
Publikováno v:
IJCNN
are applicable to user verification. We devise a two-factor system so that impersonators who hold identification numbers in fraudulence are detectable. In the first step, a subject either authentic or false tries to input a digit of a ten-key in the
Autor:
Ryota Yokote, Yasuo Matsuyama
Publikováno v:
Journal of Signal and Information Processing. :275-285
A class of rapid algorithms for independent component analysis (ICA) is presented. This method utilizes multi-step past information with respect to an existing fixed-point style for increasing the non-Gaussianity. This can be viewed as the addition o
Publikováno v:
IJCNN
Video data captured and uploaded under volatile conditions is accumulating into a flood of unstructured content that is hard to manage. In this paper, we present a set of algorithms that generate numeric or soft labels to structure automatically and
Development of a method to estimate gene functions is an important task in bioinformatics. One of the approaches for the annotation is the identification of the metabolic pathway that genes are involved in. Since gene expression data reflect various
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b6d399dc1ba9c60eea49d50fc212c12
Autor:
Yasuo Matsuyama, Naoto Katsumata
Publikováno v:
Engineering Applications of Artificial Intelligence. 18:705-717
Similar-image retrieval systems are newly presented and examined. The systems use ICA bases (independent component analysis bases) or PCA bases (principal component analysis bases). These bases can contain source image's information, however, the ind
Autor:
Yasuo Matsuyama
Publikováno v:
IEEE Transactions on Information Theory. 49:692-706
A new likelihood maximization algorithm called the /spl alpha/-EM algorithm (/spl alpha/-expectation-maximization algorithm) is presented. This algorithm outperforms the traditional or logarithmic EM algorithm in terms of convergence speed for an app