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PhD: Improving deep and machine learning using second-order information
Where: University of Technology Sydney, Australia Australia
What: Location: University of Technology Sydney – City campus. UTS is #1 young university in Australia in 2019 based on QS and THE ranking. Also, UTS is ranked #29 globally and #1 in Australia for the subject area of Computer Science and Engineering (based on 2019 ARWU rankings)

Project Detail: This project is about incorporating second-order information into machine learning methods in order to boost the initialization and learning processes. From the machine learning methods in this project, it particularly focuses on deep neural networks. Several topics are going to be investigated in this project including hybrid approaches, big data analytics, graph theory, large scale problems.

Requirements: A solid background in data and computer sciences as well as strong programming skill (MatLab/Python). A master degree in data science, computer science, mathematics, AI, engineering, or related field. Background in statistics and machine learning methods, deep learning in particular. Publications with major conferences and/or journals.

Who: https://www.uts.edu.au/staff/amirhossein.gandomi
When: Until 2020-07-30 10:00
Presented at next GECCO?: yes



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