Some Applications of Machine Learning in Edge Computing, Wireless and Mobile Systems
| dc.contributor.author | Sridhar, Anantharaghavan | |
| dc.date.accessioned | 2017-02-27T21:15:07Z | |
| dc.date.available | 2017-02-27T21:15:07Z | |
| dc.date.issued | 2017-02-27T21:15:07Z | |
| dc.description.abstract | Recent advancement in Deep Learning for Image Classification and Perception tasks have contributed to incredible advancements in consumer technology. Devices such as Google Home, projects such as self-driving cars are now closer to reality than ever, thanks to the capacity of deep learning algorithms and research. However, the systems research community has been slower to catch up with the wave of deep learning, in the areas of edge computing and wireless systems. The objective of this thesis is to expose the reader to some possible applications and ideas for applying machine learning and deep learning techniques in systems research. Particularly, the focus of this thesis is on edge computing, wireless and mobile systems where I believe there is large scope for defining new applications for machine learning research. | en |
| dc.identifier.uri | http://digital.library.wisc.edu/1793/75934 | |
| dc.language.iso | en_US | en |
| dc.title | Some Applications of Machine Learning in Edge Computing, Wireless and Mobile Systems | en |
| dc.type | Thesis | en |