Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Manh Truong Dang"'
Autor:
Tiancai Liang, Manh Truong Dang, John McCall, Alan Wee-Chung Liew, Anh Vu Luong, Tien Thanh Nguyen
Publikováno v:
Pattern Recognition. 95:96-113
With the advancement of storage and processing technology, an enormous amount of data is collected on a daily basis in many applications. Nowadays, advanced data analytics have been used to mine the collected data for useful information and make pred
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3651e8e225eb8f846015373534ce8676
https://doi.org/10.1016/j.patcog.2019.06.001
https://doi.org/10.1016/j.patcog.2019.06.001
Publikováno v:
Information Sciences. 490:36-58
In this paper, we propose a weighted multiple classifier framework based on random projections. Similar to the mechanism of other homogeneous ensemble methods, the base classifiers in our approach are obtained by a learning algorithm on different tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f62557365c2dd6c14814c0388106080f
https://doi.org/10.1016/j.ins.2019.03.067
https://doi.org/10.1016/j.ins.2019.03.067
Autor:
Nang Van Pham, Manh Truong Dang, Anh Vu Luong, Tien Thanh Nguyen, Alan Wee-Chung Liew, John McCall
Publikováno v:
GECCO
Deep Neural Networks have achieved many successes when applying to visual, text, and speech information in various domains. The crucial reasons behind these successes are the multi-layer architecture and the in-model feature transformation of deep le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df7982dd93cc3079c27fdc889981fe84
https://doi.org/10.1145/3377930.3389832
https://doi.org/10.1145/3377930.3389832
Akademický článek
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Autor:
Anh Vu Luong, Tien Thanh Nguyen, Manh Truong Dang, Thi Thu Thuy Nguyen, Alan Wee-Chung Liew, Lan Phuong Dao, John McCall
Publikováno v:
Neural Information Processing ISBN: 9783030367077
ICONIP (1)
ICONIP (1)
In this paper, we aim to develop an effective combining algorithm for ensemble learning systems. The Decision Template method, one of the most popular combining algorithms for ensemble systems, does not perform well when working on certain datasets l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34e26a9ab74fb146ca9507a2719299b6
https://doi.org/10.1007/978-3-030-36708-4_50
https://doi.org/10.1007/978-3-030-36708-4_50
Autor:
Vimal Anand Baghel, John McCall, Anh Vu Luong, Tien Thanh Nguyen, Manh Truong Dang, Alan Wee-Chung Liew
Publikováno v:
Knowledge-Based Systems. :106034
Designing an ensemble of classifiers is one of the popular research topics in machine learning since it can give better results than using each constituent member. Furthermore, the performance of ensemble can be improved using selection or adaptation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32189f7a435a6bb3a51c7621bc41f6b5
https://doi.org/10.1016/j.knosys.2020.106034
https://doi.org/10.1016/j.knosys.2020.106034
Publikováno v:
Pattern Recognition. 100:107104
Ensemble selection is one of the most studied topics in ensemble learning because a selected subset of base classifiers may perform better than the whole ensemble system. In recent years, a great many ensemble selection methods have been introduced.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f7aa3c61b0a549e8243717237aa3c7b
https://doi.org/10.1016/j.patcog.2019.107104
https://doi.org/10.1016/j.patcog.2019.107104
Autor:
Manh Truong Dang, Tuyet-Trinh Vu, Quoc Viet Hung Nguyen, Bela Stantic, Anh Vu Luong, Tien Thanh Nguyen
Publikováno v:
Intelligent Information and Database Systems ISBN: 9783319754161
ACIIDS (1)
ACIIDS (1)
In this paper, we propose using dynamic ensemble selection (DES) method on ensemble generated based on random projection. We first construct the homogeneous ensemble in which a set of base classifier is obtained by a learning algorithm on different t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e632a4284d13e2fc21843f000666fd85
https://doi.org/10.1007/978-3-319-75417-8_54
https://doi.org/10.1007/978-3-319-75417-8_54
Akademický článek
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