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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
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challenging data problem. Weak signals from collisions of compact objects can be dug out of noisy time series because we understand what the signal should look like, and can therefore use simple algorithms
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complexity), Vol. 42, No. 4 , pp270-283 Wallace, C.S. and D.L. Dowe (2000). MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions , Statistics and Computing, Vol. 10, No. 1, Jan
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-readable representations, such as distributed representations of text augmented with random noises [1] or unnatural text curated by replacing sensitive tokens with random non-sensitive ones [2]. First, such
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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-aware models and schemes for optimising distribution, storage and processing of tasks and data in each layer.
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distributions. We wish to represent the biological networks into proper formats, e.g., vector representations, so that existing machine learning algorithms (e.g., support vector machines) can readily be used
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: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement on the headspace website, enabling the generation of tailored service and resource suggestions
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input, security, and distribution in collaboration with the Research Officer Act as a key point of contact for consortium members, site investigators, and stakeholders About You: Degree in a relevant
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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind