Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Masanori Kawakita"'
Autor:
Masaru Ushijima, Satoshi Miyata, Shinto Eguchi, Masanori Kawakita, Masataka Yoshimoto, Takuji Iwase, Futoshi Akiyama, Goi Sakamoto, Koichi Nagasaki, Yoshio Miki, Tetsuo Noda, Yutaka Hoshikawa, Masaaki Matsuura
Publikováno v:
Cancer Informatics, Vol 3, Pp 285-293 (2007)
We propose a method for biomarker discovery from mass spectrometry data, improving the common peak approach developed by Fushiki et al. (BMC Bioinformatics, 7:358, 2006). The common peak method is a simple way to select the sensible peaks that are sh
Externí odkaz:
https://doaj.org/article/2e37d9863b494509ade5ff821f909c7d
Autor:
Jun'ichi Takeuchi, Takeshi Takahashi, Koji Nakao, Masanori Kawakita, Daisuke Inoue, Jumpei Shimamura, Chansu Han
Publikováno v:
TrustCom/BigDataSE
Recent malware evolutions have rendered cyberspace less secure, and we are currently witnessing an increasing number of severe security incidents. To minimize the impact of malware activities, it is important to detect them promptly and precisely. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab5fa7b4a970e10a90162922e576b67c
https://doi.org/10.1109/trustcom/bigdatase.2019.00028
https://doi.org/10.1109/trustcom/bigdatase.2019.00028
Publikováno v:
ISITA
Cardinality of typical sets and the smallest high probability set for discrete memoryless sources and stationary Markov sources are considered. Usually, its width is fixed in the definition of both sets, but sometimes it is assumed that the width con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3425f06379a0cec1a9ea43cde65768d
https://doi.org/10.23919/isita.2018.8664327
https://doi.org/10.23919/isita.2018.8664327
Publikováno v:
ISIT
For the additive white Gaussian noise channel with average power constraint, sparse superposition codes with least squares decoding are proposed by Barron and Joseph in 2010. The codewords are designed by using a dictionary each entry of which is dra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c580a8eef72d47d74cec8e641e00e31
https://doi.org/10.1109/tit.2014.2312728
https://doi.org/10.1109/tit.2014.2312728
Autor:
Masanori Kawakita, Jun'ichi Takeuchi
The risk estimator called "Direct Eigenvalue Estimator" (DEE) is studied. DEE was developed for small sample regression. In contrast to many existing model selection criteria, derivation of DEE requires neither any asymptotic assumption nor any prior
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1862fff3720b172010d9fcd72c29e01d
http://arxiv.org/abs/1610.03938
http://arxiv.org/abs/1610.03938
Autor:
Masanori Kawakita, Jun'ichi Takeuchi
The minimum description length (MDL) principle in supervised learning is studied. One of the most important theories for the MDL principle is Barron and Cover's theory (BC theory), which gives a mathematical justification of the MDL principle. The or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6570386aba8333d2a109b8ec96580133
http://arxiv.org/abs/1607.02914
http://arxiv.org/abs/1607.02914
Publikováno v:
Neural Information Processing ISBN: 9783319466866
ICONIP (1)
ICONIP (1)
A botnet detection method using the graphical lasso is studied. Hamasaki et al. proposed a botnet detection method based on graphical lasso applied on darknet traffic, which captures change points of outputs of graphical lasso caused by a botnet acti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52a175ce784551291180f018ed99e186
https://doi.org/10.1007/978-3-319-46687-3_59
https://doi.org/10.1007/978-3-319-46687-3_59
Publikováno v:
Neural Information Processing ISBN: 9783319466866
ICONIP (1)
ICONIP (1)
A method for botnet detection from traffic data of the Internet by the Non-negative Matrix Factorization (NMF) was proposed by (Yamauchi et al. 2012). This method assumes that traffic data is composed by several types of communications, and estimates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1a4526e0baa84120e529595bfc82877
https://doi.org/10.1007/978-3-319-46687-3_63
https://doi.org/10.1007/978-3-319-46687-3_63
Autor:
Shinto Eguchi, Masanori Kawakita
Publikováno v:
Neural Computation. 20:2792-2838
We propose a local boosting method in classification problems borrowing from an idea of the local likelihood method. Our proposal, local boosting, includes a simple device for localization for computational feasibility. We proved the Bayes risk consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c5a40ab12e8d65265255990923c7889
https://doi.org/10.1162/neco.2008.06-07-549
https://doi.org/10.1162/neco.2008.06-07-549
Autor:
Junnichi Takeuchi, Masanori Kawakita
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 53
We are interested in developing a safe semi-supervised learning that works in any situation. Semi-supervised learning postulates that n ′ unlabeled data are available in addition to n labeled data. However, almost all of the previous semi-supervise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1871e1804b3e6c22a717795c47719632
https://pubmed.ncbi.nlm.nih.gov/24632000
https://pubmed.ncbi.nlm.nih.gov/24632000