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Academic Articles & Research Papers
Showing 17 of 57 academic articles
Li Deng • APSIPA Transactions on Signal and Information Processing
(2014)
In this invited paper, my overview material on the same topic as presented in the plenary overview session of APSIPA-2011 and the tutorial material presented in the same conference [1] are expanded and updated to include more recent develop...
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DOI: https://doi.org/10.1017/atsip.2013.9
Nir Shlezinger, Yonina C. Eldar, Stephen Boyd • IEEE Access
(2022)
Decision making algorithms are used in a multitude of different applications. Conventional approaches for designing decision algorithms employ principled and simplified modelling, based on which one can determine decisions via tractable opt...
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DOI: https://doi.org/10.1109/access.2022.3218802
Chaoyun Zhang, Paul Patras, Hamed Haddadi • IEEE Communications Surveys & Tutorials
(2019)
The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traff...
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Open Access
DOI: https://doi.org/10.1109/comst.2019.2904897
Richard J. Roiger • Chapman & Hall/CRC eBooks
(2020)
R is one of the top-rated problem-solving tools for machine learning, data science, data analytics, data mining, and statistical analysis. R ’s popularity has resulted in the development of thousands of tutorials. Unfortunately, it’s easy t...
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DOI: https://doi.org/10.1201/9781003006695-1
Ral Garreta, Guillermo Moncecchi • International Linear Collider
(2013)
The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this...
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Matthias Seeger • International Journal of Neural Systems
(2004)
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...
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Open Access
DOI: https://doi.org/10.1142/s0129065704001899
William W. Cohen, Andrew McCallum, Sam T. Roweis (2008)
This volume contains the papers accepted to the 25th International Conference on Machine Learning (ICML 2008). ICML is the annual conference of the International Machine Learning Society (IMLS), and provides a venue for the presentation and...
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Sergios Theodoridis (2015)
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabil...
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William W. Cohen, Andrew Moore (2006)
This volume, which is also available from http://www.machinelearning.org, the home page of the International Machine Learning Society, contains the technical papers accepted for presentation at ICML-2006, the 23rd International Conference o...
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Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong • Cambridge University Press eBooks
(2020)
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in d...
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DOI: https://doi.org/10.1017/9781108679930
(2007)
This volume contains the papers accepted to the 24th International Conference on Machine Learning (ICML 2007), which was held at Oregon State University in Corvalis, Oregon, from June 20th to 24th, 2007. ICML is the annual conference of the...
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DOI: https://doi.org/10.1145/1273496
Adi Laurentiu Tarca, Vincent J. Carey, Xuewen Chen, Roberto J. Romero et al. • PLoS Computational Biology
(2007)
The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...
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public-domain
DOI: https://doi.org/10.1371/journal.pcbi.0030116
PMC: 1904382
Joshua I. Glaser, Ari S. Benjamin, Raeed H. Chowdhury, Matthew G. Perich et al. • eNeuro
(2020)
Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve deco...
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DOI: https://doi.org/10.1523/eneuro.0506-19.2020
PMC: 7470933
Peter de B. Harrington (2012)
SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...
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Ian Millington, John Funge • CRC Press eBooks
(2018)
Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional ex...
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DOI: https://doi.org/10.1201/9781315375229
Ian Millington • CRC Press eBooks
(2009)
Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional ex...
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DOI: https://doi.org/10.1201/b13169
Sameer Qazi, Bilal A. Khawaja, Qazi Umar Farooq • IEEE Access
(2022)
Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2022.3152544