Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Mohamed Al Mashrgy"'
Autor:
Simge Akay, Basim Alghabashi, Mohamed Al Mashrgy, Nafiz Arica, Zeinab Arjmandiasl, Muhammad Azam, B. Balasingam, Jamal Bentahar, F. Biondi, Aaron Boda, Nizar Bouguila, Duygu Cakir, Mark Green, Sorin Grigorescu, Baoxin Hu, Xishi Huang, M. Khalghollah, Howard Li, C.J.B. Macnab, Narges Manouchehri, Jun Meng, Afshin Rahimi, P. Ramakrishnan, Jing Ren, Jianguo Wang, Jin Wang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79626e32df85d4b5d107eafae2610d8b
https://doi.org/10.1016/b978-0-12-822314-7.00005-5
https://doi.org/10.1016/b978-0-12-822314-7.00005-5
Model-based approaches have been widely utilized to investigate multi-dimensional positive features for the purpose of gaining beneficial knowledge. In fact, feature selection is a critical and challenging task when modeling data that are represented
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f381366400d8c976a3c6451e306c9b5
https://doi.org/10.1016/b978-0-12-822314-7.00011-0
https://doi.org/10.1016/b978-0-12-822314-7.00011-0
Autor:
Mohamed Al Mashrgy, Sami Bourouis, Nizar Bouguila, Hassen Sallay, Fahd M. Aldosari, Faisal R. Al-Osaimi
Publikováno v:
Soft Computing. 23:5799-5813
The goal of constructing models from examples has been approached from different perspectives. Statistical methods have been widely used and proved effective in generating accurate models. Finite Gaussian mixture models have been widely used to descr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40dea147a92869e7d0c7c11c20fa4922
https://doi.org/10.1007/s00500-018-3244-4
https://doi.org/10.1007/s00500-018-3244-4
Autor:
Sami Bourouis, Fahd M. Aldosari, Faisal R. Al-Osaimi, Mohamed Al Mashrgy, Nizar Bouguila, Hassen Sallay
Publikováno v:
AICCSA
We propose a Bayesian approach to learn finite generalized inverted Dirichlet mixture models. The developed approach performs simultaneous parameters estimation, model complexity determination, and feature selection via a reversible jump Markov Chain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c1040c8652aa099db92be3e3e36a5f5
https://doi.org/10.1109/aiccsa.2017.43
https://doi.org/10.1109/aiccsa.2017.43
Publikováno v:
Expert Systems with Applications. 41:2329-2336
The advent of mixture models has opened the possibility of flexible models which are practical to work with. A common assumption is that practitioners typically expect that data are generated from a Gaussian mixture. The inverted Dirichlet mixture ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4b843eba3f29a3772b5977fe88bc32c
https://doi.org/10.1016/j.eswa.2013.09.030
https://doi.org/10.1016/j.eswa.2013.09.030
Publikováno v:
Knowledge-Based Systems. 59:182-195
The discovery, extraction and analysis of knowledge from data rely generally upon the use of unsupervised learning methods, in particular clustering approaches. Much recent research in clustering and data engineering has focused on the consideration
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d40636df502bc2a18086e9452afb53b
https://doi.org/10.1016/j.knosys.2014.01.007
https://doi.org/10.1016/j.knosys.2014.01.007
Autor:
Nizar Bouguila, Mohamed Al Mashrgy
Publikováno v:
Studies in Computational Intelligence ISBN: 9783319198323
Artificial Intelligence Applications in Information and Communication Technologies
Artificial Intelligence Applications in Information and Communication Technologies
The main concern with mixture modeling is to describe data in which each observation belongs to one of some number of different groups. Mixtures of distributions provide a flexible and convenient class of models for density estimation and their stati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70248ca1741505e6e6d2a9d857af8a78
https://doi.org/10.1007/978-3-319-19833-0_7
https://doi.org/10.1007/978-3-319-19833-0_7
Autor:
Nizar Bouguila, Mohamed Al Mashrgy
Publikováno v:
Information and Communication Technology ISBN: 9783642550317
ICT-EurAsia
Lecture Notes in Computer Science
2nd Information and Communication Technology-EurAsia Conference (ICT-EurAsia)
2nd Information and Communication Technology-EurAsia Conference (ICT-EurAsia), Apr 2014, Bali, Indonesia. pp.296-305, ⟨10.1007/978-3-642-55032-4_29⟩
ICT-EurAsia
Lecture Notes in Computer Science
2nd Information and Communication Technology-EurAsia Conference (ICT-EurAsia)
2nd Information and Communication Technology-EurAsia Conference (ICT-EurAsia), Apr 2014, Bali, Indonesia. pp.296-305, ⟨10.1007/978-3-642-55032-4_29⟩
Part 1: Information & Communication Technology-EurAsia Conference 2014, ICT-EurAsia 2014; International audience; We propose an infinite mixture model for the clustering of positive data. The proposed model is based on the generalized inverted Dirich
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88289956a2c649aafec8cdacc9e1907a
https://doi.org/10.1007/978-3-642-55032-4_29
https://doi.org/10.1007/978-3-642-55032-4_29
Publikováno v:
Neural Information Processing ISBN: 9783642249570
ICONIP (2)
International Conference on Neural Information Processing (ICONIP)
International Conference on Neural Information Processing (ICONIP), Nov 2011, Shanghai, China
ICONIP (2)
International Conference on Neural Information Processing (ICONIP)
International Conference on Neural Information Processing (ICONIP), Nov 2011, Shanghai, China
International audience; Given a set of binary vectors drawn from a ¯nite multiple Bernoulli mixture model, an important problem is to determine which vectors are outliers and which features are relevant. The goal of this paper is to propose a model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19740e424549d686546e5f65276b1730
https://doi.org/10.1007/978-3-642-24958-7_15
https://doi.org/10.1007/978-3-642-24958-7_15