Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Thahir Mohamed"'
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
Intelligent personal assistants (IPA) enable voice applications that facilitate people's daily tasks. However, due to the complexity and ambiguity of voice requests, some requests may not be handled properly by the standard natural language understan
Externí odkaz:
https://doaj.org/article/5277a6b3debd42bf91bdd86b724e619f
Autor:
Qian Hu, Thahir Mohamed, Wei Xiao, Xiyao Ma, Xibin Gao, Zheng Gao, Radhika Arava, Mohamed AbdelHady
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
Intelligent personal assistants (IPAs) such as Amazon Alexa, Google Assistant and Apple Siri extend their built-in capabilities by supporting voice apps developed by third-party developers. Sometimes the smart assistant is not able to successfully re
Externí odkaz:
https://doaj.org/article/b9f76b3cbeae459481c600de35f76302
Publikováno v:
BMC Proceedings, Vol 6, Iss Suppl 7, p S2 (2012)
Abstract Background Machine learning approaches for classification learn the pattern of the feature space of different classes, or learn a boundary that separates the feature space into different classes. The features of the data instances are usuall
Externí odkaz:
https://doaj.org/article/10832f1ba995494795fce31592365028
Publikováno v:
2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU).
Publikováno v:
Interspeech 2021.
Publikováno v:
Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI.
Autor:
Tom Mitchell, William Cohen, Estevam Hruschka, Partha Talukdar, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matthew Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapa Nakashole, Emmanouil Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 29
Whereas people learn many different types of knowledge from diverse experiences over many years, most current machine learning systems acquire just a single function or data model from just a single data set. We propose a never-ending learning paradi
Akademický článek
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Akademický článek
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Autor:
Ganapathiraju MK; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Intelligent Systems Program, School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA, USA., Thahir M; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Intelligent Systems Program, School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA, USA., Handen A; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh , Pittsburgh, PA, USA., Sarkar SN; Department of Microbiology and Molecular Genetics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Cancer Virology Program, University of Pittsburgh Cancer Institute, Pittsburgh, PA, USA., Sweet RA; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA., Nimgaonkar VL; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA., Loscher CE; Immunomodulation Research Group, School of Biotechnology, Dublin City University , Dublin, Ireland., Bauer EM; Department of Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, PA, USA., Chaparala S; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh , Pittsburgh, PA, USA.
Publikováno v:
NPJ schizophrenia [NPJ Schizophr] 2016 Apr 27; Vol. 2, pp. 16012. Date of Electronic Publication: 2016 Apr 27 (Print Publication: 2016).