Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Yanhuang Jiang"'
Autor:
Yanhuang Jiang, Chengkun Wu, Yanghui Zhang, Shaowei Zhang, Shuojun Yu, Peng Lei, Qin Lu, Yanwei Xi, Hua Wang, Zhuo Song
Publikováno v:
BMC Medical Genomics, Vol 12, Iss S8, Pp 1-10 (2019)
Abstract Background An important task in the interpretation of sequencing data is to highlight pathogenic genes (or detrimental variants) in the field of Mendelian diseases. It is still challenging despite the recent rapid development of genomics and
Externí odkaz:
https://doaj.org/article/0e887871f3054b3fa5d6c9efc19cf480
Publikováno v:
KES
Term weight algorithms based on inverse document analysis are widely used in the expression of characteristic information for text. According to the finding that frequently occurring terms always cover less feature information for the text, the terms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78687afc0fbd3a4a73aba432b80dc448
https://doi.org/10.1016/j.procs.2020.09.079
https://doi.org/10.1016/j.procs.2020.09.079
Autor:
Zhang Shaowei, Hua Wang, Zhuo Song, Yanwei Xi, Chengkun Wu, Yanhuang Jiang, Yanghui Zhang, Yu Shuojun, Qin Lu, Lei Peng
Publikováno v:
BMC Medical Genomics
BMC Medical Genomics, Vol 12, Iss S8, Pp 1-10 (2019)
BMC Medical Genomics, Vol 12, Iss S8, Pp 1-10 (2019)
Background An important task in the interpretation of sequencing data is to highlight pathogenic genes (or detrimental variants) in the field of Mendelian diseases. It is still challenging despite the recent rapid development of genomics and bioinfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a2214c0bd0670e68bf971cb959c1760
https://doi.org/10.1186/s12920-019-0637-x
https://doi.org/10.1186/s12920-019-0637-x
Publikováno v:
Artificial Intelligence Science and Technology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ccde9f46fb8e1c662290db4a370394d0
https://doi.org/10.1142/9789813206823_0064
https://doi.org/10.1142/9789813206823_0064
Publikováno v:
Mathematical Problems in Engineering, Vol 2015 (2015)
Combining several classifiers on sequential chunks of training instances is a popular strategy for data stream mining with concept drifts. This paper introduces human recalling and forgetting mechanisms into a data stream mining system and proposes a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d1c90d8920138d92ff84b034b638408
Autor:
Yanhuang Jiang, Chengkun Wu, Yanghui Zhang, Shaowei Zhang, Shuojun Yu, Peng Lei, Qin Lu, Yanwei Xi, Hua Wang, Zhuo Song
Publikováno v:
BMC Medical Genomics; 12/20/2019 Supplement 8, Vol. 12, p1-10, 10p, 5 Diagrams, 2 Graphs
Autor:
Yanhuang Jiang, Qiangli Zhao
Publikováno v:
ICDM Workshops
Compared to single classifiers, ensemble learning offers significant and stable performance improvement, while ensemble pruning can improve efficiency and performance of the ensembles further, so both of them are hot topics, not only in traditional m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54b6b59f85c55265c5749ea3a9d17d82
https://doi.org/10.1109/icdmw.2014.52
https://doi.org/10.1109/icdmw.2014.52
Autor:
Yanhuang Jiang, Hao Zhou
Publikováno v:
CyberC
The reliability issue of Exascale system is extremely serious. Traditional passive fault-tolerant methods, such as rollback-recovery, can not fully guarantee system reliability any more because of their large executing overhead and long recovering du
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5764095a05b986a73ec47c71bc445bfd
https://doi.org/10.1109/cyberc.2011.68
https://doi.org/10.1109/cyberc.2011.68
Publikováno v:
2009 Sixth Web Information Systems and Applications Conference.
When disaster happens, it is necessary to employ efficient and accurate methods to select the best service from many service backed sites to control DR (Disaster Recovery) activities. Aim at the service deployment algorithm is not suit for MultiObjec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b5b17c065d1e3349d2a66aee15ecbdc
https://doi.org/10.1109/wisa.2009.37
https://doi.org/10.1109/wisa.2009.37
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540200543
APPT
APPT
Image resampling is an important and computation-intensive task in many fields. In order to improve its efficiency, a distributed parallel resampling algorithm with good data locality is provided, in which each processor entirely localizes its comput
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1e7d6ba192b123fcdacc8d8a0dd3075
https://doi.org/10.1007/978-3-540-39425-9_71
https://doi.org/10.1007/978-3-540-39425-9_71
