Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Ken Ueno"'
Publikováno v:
Engineering Proceedings, Vol 39, Iss 1, p 82 (2023)
The problem of anomaly detection in time series has recently received much attention, but in most practical applications, labels for normal and anomalous data are not available. Furthermore, reasons for anomalous results must often be determined. In
Externí odkaz:
https://doaj.org/article/1d8338cd599f45a49f30820528f4faa9
Autor:
Ken Ueno
Publikováno v:
The Oxford Handbook of Spectral Music ISBN: 9780190633547
This chapter examines two “person-specific” concertos by Ken Ueno: On a Sufficient Condition for the Existence of Most Specific Hypothesis (2008), a vocal concerto featuring the composer himself as soloist, and Zetsu (2015), a chamber concerto wr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a55824ac45db0f859c034760202cb53
https://doi.org/10.1093/oxfordhb/9780190633547.013.47
https://doi.org/10.1093/oxfordhb/9780190633547.013.47
Autor:
Topon Paul, Sreeharsha Raghavendra, Ken Ueno, Fang Ni, Hiromasa Shin, Kaneharu Nishino, Ryusei Shingaki
Publikováno v:
2021 International Conference on Data Mining Workshops (ICDMW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea093113422c1208dbe5f32c04802f3e
https://doi.org/10.1109/icdmw53433.2021.00074
https://doi.org/10.1109/icdmw53433.2021.00074
Publikováno v:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c607f330076f6b85e276ca71b58944f8
https://doi.org/10.1109/icmla52953.2021.00188
https://doi.org/10.1109/icmla52953.2021.00188
Publikováno v:
International Journal of Data Science and Analytics. 8:137-164
In this paper, we propose delayed Long Short-Term Memory (dLSTM), an anomaly detection method for time-series data. We first build a predictive model from normal (non-anomalous) training data, then perform anomaly detection based on the prediction er
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95f7a1862b3af8bc65995ffac3bf7d33
https://doi.org/10.1007/s41060-019-00186-0
https://doi.org/10.1007/s41060-019-00186-0
Autor:
Ken Ueno
Publikováno v:
Solid State Circuits Technologies
In this chapter, overviews of previous reported low-power reference circuits and details of our circuits were provided. These circuits generate constant reference voltages and currents that are independent of supply voltage and temperature. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a7477ad59db414302467301e993e297
http://www.intechopen.com/articles/show/title/cmos-voltage-and-current-reference-circuits-consisting-of-subthreshold-mosfets-micropower-circuit-co
http://www.intechopen.com/articles/show/title/cmos-voltage-and-current-reference-circuits-consisting-of-subthreshold-mosfets-micropower-circuit-co
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676575
ECML/PKDD (1)
ECML/PKDD (1)
Shapelets are time-series segments effective for classifying time-series instances. Joint learning of both classifiers and shapelets has been studied in recent years because such a method provides both superior classification performance and interpre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17963348952e7e719ea6c8827a65573e
https://doi.org/10.1007/978-3-030-67658-2_34
https://doi.org/10.1007/978-3-030-67658-2_34
Autor:
Akihiro Yamaguchi, Ken Ueno
Publikováno v:
Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) ISBN: 9781611976700
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b8e3362ca6efe7ae502492725a21248
https://doi.org/10.1137/1.9781611976700.30
https://doi.org/10.1137/1.9781611976700.30
Autor:
Ken Ueno
Publikováno v:
Fractured Scenes ISBN: 9789811559129
This chapter paints a personal and affective panorama of the Hong Kong underground. In the context of Hong Kong, music making is described as the making of radically contextual musical instruments and as an escape from anonymizing global forces. It p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2ddb1484db8d44bcb2f96ed469afc6d
https://doi.org/10.1007/978-981-15-5913-6_2
https://doi.org/10.1007/978-981-15-5913-6_2