A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks

Yingxu WANG; Henry LEUNG; Marina GAVRILOVA; Omar ZATARAIN; Daniel GRAVES; Jianhua LU; Newton HOWARD; Sam KWONG; Phillip SHEU; Shushma PATEL

doi:10.1109/ICCI-CC.2018.8482022

A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks

Yingxu WANG, Henry LEUNG, Marina GAVRILOVA, Omar ZATARAIN, Daniel GRAVES, Jianhua LU, Newton HOWARD, Sam KWONG, Phillip SHEU, Shushma PATEL

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

8 Citations (Scopus)

Abstract

Sequence learning is one of the hard challenges to current machine learning technologies and deep neural network technologies. This paper presents a literature survey and analysis on a variety of neural networks towards sequence learning. The conceptual models, methodologies, mathematical models and usages of classic neural networks and their learning capabilities are contrasted. Advantages and disadvantages of neural networks for sequence learning are formally analyzed. The state-of-the-art, theoretical problems and technical constraints of existing methodologies are reviewed. The needs for understanding temporal sequences by unsupervised or intensive-training-free learning theories and technologies are elaborated.

Original language	English
Title of host publication	Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018
Pages	42156
DOIs	https://doi.org/10.1109/ICCI-CC.2018.8482022
Publication status	Published - Jul 2018
Externally published	Yes

Keywords

Analytic methodologies
Applications
Cognitive systems
Deep NNs
Denotational mathematics
Language sequence learning
Neural networks (NNs)
Recurrent NNs
Sequence learning
Visual sequence learning

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10.1109/ICCI-CC.2018.8482022

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WANG, Y., LEUNG, H., GAVRILOVA, M., ZATARAIN, O., GRAVES, D., LU, J., HOWARD, N., KWONG, S., SHEU, P., & PATEL, S. (2018). A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks. In Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 (pp. 42156) https://doi.org/10.1109/ICCI-CC.2018.8482022

@inproceedings{4be17dcca8264dbfa1800865fb36af97,

title = "A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks",

abstract = "Sequence learning is one of the hard challenges to current machine learning technologies and deep neural network technologies. This paper presents a literature survey and analysis on a variety of neural networks towards sequence learning. The conceptual models, methodologies, mathematical models and usages of classic neural networks and their learning capabilities are contrasted. Advantages and disadvantages of neural networks for sequence learning are formally analyzed. The state-of-the-art, theoretical problems and technical constraints of existing methodologies are reviewed. The needs for understanding temporal sequences by unsupervised or intensive-training-free learning theories and technologies are elaborated.",

keywords = "Analytic methodologies, Applications, Cognitive systems, Deep NNs, Denotational mathematics, Language sequence learning, Neural networks (NNs), Recurrent NNs, Sequence learning, Visual sequence learning",

author = "Yingxu WANG and Henry LEUNG and Marina GAVRILOVA and Omar ZATARAIN and Daniel GRAVES and Jianhua LU and Newton HOWARD and Sam KWONG and Phillip SHEU and Shushma PATEL",

year = "2018",

month = jul,

doi = "10.1109/ICCI-CC.2018.8482022",

language = "English",

pages = "42156",

booktitle = "Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018",

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WANG, Y, LEUNG, H, GAVRILOVA, M, ZATARAIN, O, GRAVES, D, LU, J, HOWARD, N, KWONG, S, SHEU, P & PATEL, S 2018, A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks. in Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018. pp. 42156. https://doi.org/10.1109/ICCI-CC.2018.8482022

A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks. / WANG, Yingxu; LEUNG, Henry; GAVRILOVA, Marina et al.
Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018. 2018. p. 42156.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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AU - GAVRILOVA, Marina

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AU - GRAVES, Daniel

AU - LU, Jianhua

AU - HOWARD, Newton

AU - KWONG, Sam

AU - SHEU, Phillip

AU - PATEL, Shushma

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KW - Applications

KW - Cognitive systems

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KW - Denotational mathematics

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SP - 42156

BT - Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018

ER -

A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks

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