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guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
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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
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Learning, Algorithms and Data Structures
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models (eg auto-encoders and generative adversarial networks) and reinforcement/imitation learning algorithms for Markov Decision Processes. The application areas are different problems in text processing
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Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention. Despite many studies introducing various APR techniques, much remains to be learned, however, about...
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headlines around the world when a “work of art created by an algorithm” was sold at auction by Christie’s for $432,500 – nearly 45 times the value estimated before auction. It turned out that the group behind
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on this technology for its automated warehouses and fulfilment centres. The aim of this project is to use discrete optimisation techniques (e.g. Integer Programming) to design new algorithms for MAPF. An example
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Mixed-Integer Programming (MIP) solvers are very powerful tools to solve combinatorial problems that arise in many industries. Modern MIP solvers usually run a sequence of algorithms to solve