Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Eddie Xu"'
Autor:
Jodi Wong, Stephen Yiu Chuen Choi, Rongrong Liu, Eddie Xu, James Killam, Peter W. Gout, Yuzhuo Wang
Publikováno v:
Frontiers in Cellular and Infection Microbiology, Vol 9 (2019)
Many global infectious diseases are not well-controlled, underlining a critical need for new, more effective therapies. Pathogens and pathogen-infected host cells, like cancer cells, evade immune surveillance via immune evasion mechanisms. The presen
Externí odkaz:
https://doaj.org/article/6531244f7bd94fd5b1387c69a6c5ca1f
Autor:
Stephen Yiu Chuen Choi, Peter W. Gout, Liu Rongrong, James Killam, Jodi Wong, Eddie Xu, Yuzhuo Wang
Publikováno v:
Frontiers in Cellular and Infection Microbiology, Vol 9 (2019)
Frontiers in Cellular and Infection Microbiology
Frontiers in Cellular and Infection Microbiology
Many global infectious diseases are not well-controlled, underlining a critical need for new, more effective therapies. Pathogens and pathogen-infected host cells, like cancer cells, evade immune surveillance via immune evasion mechanisms. The presen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cc55719fa8e02dd6a6608371312f414
https://www.frontiersin.org/article/10.3389/fcimb.2019.00025/full
https://www.frontiersin.org/article/10.3389/fcimb.2019.00025/full
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 28
During the past decade, machine learning algorithms have become commonplace in large-scale real-world industrial applications. In these settings, the computation time to train and test machine learning algorithms is a key consideration. At training-t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::552e85bbf2ed26d1f2767679bc81a6aa
https://doi.org/10.1609/aaai.v28i1.8967
https://doi.org/10.1609/aaai.v28i1.8967
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783662448472
ECML/PKDD (1)
ECML/PKDD (1)
The Minimax Probability Machine (MPM) is an elegant machine learning algorithm for inductive learning. It learns a classifier that minimizes an upper bound on its own generalization error. In this paper, we extend its celebrated inductive formulation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c310ec9594087729c69b902f87b525ac
https://doi.org/10.1007/978-3-662-44848-9_37
https://doi.org/10.1007/978-3-662-44848-9_37
