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All Outputs (9)

Machine learning for voice recognition (2017)
Presentation / Conference Contribution
Kinkiri, S., Melis, W. J., & Keates, S. (2017). Machine learning for voice recognition. In The Second Medway Engineering Conference on Systems: Efficiency, Sustainability and Modelling

Verbal communication is very important to us humans, but using thisperforming verbal communication to communicateion with machines still faces particular challenges. Therefore, researchers are trying to find ways to make communication with a machine... Read More about Machine learning for voice recognition.

Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information (2017)
Presentation / Conference Contribution
Kinch, M. W., Melis, W. J., & Keates, S. (2017). Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information. In The Second Medway Engineering Conference on Systems: Efficiency, Sustainabi

This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context... Read More about Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information.

Generalized proportional fair (GPF) scheduler for LTE-A (2017)
Presentation / Conference Contribution
Aramide, S. O., Barakat, B., Wang, Y., Keates, S., & Arshad, K. (2017). Generalized proportional fair (GPF) scheduler for LTE-A. In 2017 9th Computer Science and Electronic Engineering (CEEC) (128-132). https://doi.org/10.1109/CEEC.2017.8101612

The growth of wireless traffic and the demand for higher data rates motivated researchers around the world to enhance the Long Term Evolution-Advanced (LTE-A) performance. Recently, a considerable amount of the research had been done to optimise the... Read More about Generalized proportional fair (GPF) scheduler for LTE-A.

Advances in Manufacturing Technology XXXI (2017)
Presentation / Conference Contribution
(2017). Advances in Manufacturing Technology XXXI. In X. Gao, M. E. Souri, & S. Keates (Eds.), Proceedings of the 15th International Conference on Manufacturing Research, incorporating the 32nd National Conference on Manufacturing Research

No abstract available. Official url https://www.iospress.nl/book/advances-in-manufacturing-technology-xxxi/

Robotic assistants for universal access (2017)
Presentation / Conference Contribution
Keates, S., & Kyberd, P. J. (2017). Robotic assistants for universal access. In UAHCI 2017: Universal Access in Human?Computer Interaction. Human and Technological Environments (527-538). https://doi.org/10.1007/978-3-319-58700-4_43

Much research is now focusing on how technology is moving away from the traditional computer to a range of smart devices in smart environments, the so-called Internet of Things. With this increase in computing power and decrease in form factor, we ar... Read More about Robotic assistants for universal access.

Simultaneous Bayesian Clustering and Feature Selection Through Student’s ${t}$ Mixtures Model (2017)
Presentation / Conference Contribution
Sun, J., Zhou, A., Keates, S., & Liao, S. (2018). Simultaneous Bayesian Clustering and Feature Selection Through Student’s ${t}$ Mixtures Model. IEEE Transactions on Neural Networks and Learning Systems, 29(4), 1187-1199. https://doi.org/10.1109/tnnls.2

In this paper, we proposed a generative model for feature selection under the unsupervised learning context. The model assumes that data are independently and identically sampled from a finite mixture of Student?s t distributions, which can reduce th... Read More about Simultaneous Bayesian Clustering and Feature Selection Through Student’s ${t}$ Mixtures Model.

Native architecture for artificial intelligence (2017)
Presentation / Conference Contribution
Balisson, D., Melis, W. J., & Keates, S. (2017, February). Native architecture for artificial intelligence. Paper presented at 1st HBP Student Conference: Transdisciplinary Reserach Linking Neuroscience, Brain Medicine and Computer Science., Vienna, Austr

Introduction The brain is a complex organ and even to this date, very little is known about how it works. Through the years, replicating the intelligence of the brain has puzzled many scientists, and most of this work can be broadly classified into... Read More about Native architecture for artificial intelligence.

Creating patterns for machine learning using multiple alignment (2017)
Presentation / Conference Contribution
Kinkiri, S., Melis, W. J., & Keates, S. (2017, February). Creating patterns for machine learning using multiple alignment. Poster presented at First HBP (Human Brain Project) Student Conference: Transdisciplinary Research Linking Neuroscience, Brain Medic

No abstract available.