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energy resources. The expected outcomes include technical advancement of distributed algorithms for managing energy resources at customer premises. The benefits include more resilient, secure, private, and
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cryptography, quantum algorithms and cryptography, foundational theory and mathematics, and the design and analysis of cryptographic primitives and protocols, contributing to high-impact research outcomes and
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publicly available datasets; 3) Proposing algorithms aimed at improving the accuracy of human activity detection; 4) Implementing these algorithms, evaluating their performance empirically, and comparing
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cryptography, quantum algorithms and cryptography, and the design and analysis of cryptographic primitives and protocols, while playing a key role in advancing the School’s research profile, industry engagement
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. With the widespread adoption of ML algorithms for data analysis and decision-making, preserving the privacy of individuals' data has become a paramount concern. The project focuses on exploring
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The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
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. Wallace (1996). MML estimation of the parameters of the spherical Fisher Distribution. In S. Arikawa and A. K. Sharma (eds.), Proc. 7th International Workshop on Algorithmic Learning Theory (ALT'96
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: Australian History, Military History, Gender History, History of Religion Biomedical Science Ecology and Evolutionary Biology Social Work Psychology Biogeochemistry/analytical chemistry Tenure: Six-week
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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The existing deep learning based time series classification (TSC) algorithms have some success in multivariate time series, their accuracy is not high when we apply them on brain EEG time series (65