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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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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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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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known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
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theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
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strong out-of-distribution generalization capability [2]. If user-specific information is identified and removable from the input data, the devised techniques can also be applied for privacy-sensitive
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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techniques to design new and efficient algorithms that can provide strong protection during the entire life cycle of ML models used on the devices. Research Task I: Investigate ML algorithms and optimisations
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Since the 1990s, researchers have known that commonly-used public-key cryptosystems (such as RSA and Diffie-Hellman systems) could be potentially broken using an efficient algorithm running on a
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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