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Addressing practical challenges of Bayesian optimisation

Nguyen, Thanh Dai 2019, Addressing practical challenges of Bayesian optimisation, PhD thesis, School of Information Technology, Deakin University.

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Title Addressing practical challenges of Bayesian optimisation
Author Nguyen, Thanh DaiORCID iD for Nguyen, Thanh Dai orcid.org/0000-0002-7298-5035
Institution Deakin University
School School of Information Technology
Faculty Faculty of Science, Engineering and Built Environment
Degree type Research doctorate
Degree name PhD
Thesis advisor Gupta, SunilORCID iD for Gupta, Sunil orcid.org/0000-0002-3308-1930
Rana, SantuORCID iD for Rana, Santu orcid.org/0000-0003-2247-850X
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Date submitted 2019-03-19
Summary This thesis focuses on addressing several challenges in applying Bayesian optimisation in real world problems. The contributions of this thesis are new Bayesian optimisation algorithms for three practical problems: finding stable solutions, optimising cascaded processes and privacy-aware optimisation.
Language eng
Indigenous content off
Field of Research 080109 Pattern Recognition and Data Mining
170203 Knowledge Representation and Machine Learning
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
Description of original 135 p.
Copyright notice ┬ęThe author
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30130978

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Created: Tue, 29 Oct 2019, 11:33:19 EST by Penny Mcevoy

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.