Zobrazeno 1 - 10
of 65
pro vyhledávání: '"DAICHI AMAGATA"'
Publikováno v:
IEEE Access, Vol 11, Pp 2586-2596 (2023)
The problem of maximum inner product search (MIPS) is one of the most important components in machine learning systems. However, this problem does not care about diversity, although result diversification can improve user satisfaction. This paper hen
Externí odkaz:
https://doaj.org/article/26b9c3442c32492bacfe7291ebbd7cbe
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 3, Pp 208-216 (2022)
This article addresses the problem of cardinality estimation in inner product spaces. Given a set of high-dimensional vectors, a query, and a threshold, this problem estimates the number of vectors such that their inner products with the query are no
Externí odkaz:
https://doaj.org/article/0f8f1f7a6013443aad9a285f90dd6150
Publikováno v:
IEEE Access, Vol 10, Pp 55298-55307 (2022)
Due to the proliferation of location-based services, spatial data analysis becomes more and more important. We consider graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance b
Externí odkaz:
https://doaj.org/article/22c254bf5e304b2e88dd9a3c75b68a18
Autor:
Yiming Tian, Takuya Maekawa, Joseph Korpela, Daichi Amagata, Takahiro Hara, Sakiko Matsumoto, Ken Yoda
Publikováno v:
Animal Biotelemetry, Vol 9, Iss 1, Pp 1-15 (2021)
Abstract Background Recent advances in sensing technologies have enabled us to attach small loggers to animals in their natural habitat. It allows measurement of the animals’ behavior, along with associated environmental and physiological data and
Externí odkaz:
https://doaj.org/article/aeb7a12bce494f4dbcea07b97ad4c625
Autor:
Hanxin Wang, Daichi Amagata, Takuya Makeawa, Takahiro Hara, Niu Hao, Kei Yonekawa, Mori Kurokawa
Publikováno v:
IEEE Open Journal of the Industrial Electronics Society, Vol 1, Pp 194-206 (2020)
Many applications use recommender systems to predict user preferences, improve user experience, and increase the amount of sales. However, because of the cold-start problem, it is not easy to recommend items to new users accurately. Recommendation pe
Externí odkaz:
https://doaj.org/article/ccb9df0e91e74589ad15554edc152d4a
Publikováno v:
IEEE Access, Vol 6, Pp 22958-22969 (2018)
Location-based services (LBSs) have been becoming more common due to the prevalence of GPS-enabled devices. While LBSs bring many benefits for our daily lives, location information may reveal private information, rendering an important problem of pro
Externí odkaz:
https://doaj.org/article/b02fb4a8be604080a1a4abfdc3a60d16
Autor:
DAICHI AMAGATA, TAKAHIRO HARA
Publikováno v:
ACM Transactions on Knowledge Discovery from Data; Jan2024, Vol. 18 Issue 1, p1-27, 27p
Autor:
DAICHI AMAGATA, TAKAHIRO HARA
Publikováno v:
ACM Transactions on the Web; Nov2023, Vol. 17 Issue 4, p1-23, 23p
Autor:
Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783031333798
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a542624ca00819483559174c2c73fe69
https://doi.org/10.1007/978-3-031-33380-4_21
https://doi.org/10.1007/978-3-031-33380-4_21
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).