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approximation algorithms for deriving dual bound within a branch-and-bound algorithms. Other directions could use Machine Learning or new decompositions. This subject is generally quite open so it is important to
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PETs: This aspect requires a significant math background as it involves exploiting various mathematical results to develop a concrete cryptographic algorithm. Although desired, background in advanced
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science conference [1]; one of our papers is recognised as Clarivate Web of Science HighCite (top 1% of papers for the field of research) [2]; three of our algorithms (TS-Chief, InceptionTime and Rocket
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of fixing defects and the workload among software engineers. This project is aligned with Prof John Grundy (2019 ARC Laureate Fellow, Human-Centric Model-Driven Requirement Engineering) and Dr Chakkrit
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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This project will investigate and develop the ways in which AI algorithms and practices can be made transparent and explainable for use in law enforcement and judicial applications The Faculty
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as networks or graphs in the hope of reasoning about them - but the tools that we have for understanding such network structured data (whether algorithmic analytics or visualisation tools) remain crude
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Connected Autonomous Vehicle (MCAV) team. Required knowledge Artificial Intelligence Machine learning Software Testing Genetic Algorithms
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Publications: Ferrer-Mestres, J., Dietterich, T. G., Buffet, O., & Chades, I. (2020, June). Solving k-mdps. In Proceedings of the International Conference on Automated Planning and Scheduling (Vol. 30, pp. 110
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. If successful, you will join Dr. Roberto-Martinez Maldonado , Prof. Dragan Gasevic , and a strong team of academics, researchers and other students at the Centre of Learning Analytics at Monash University