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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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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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systems are based on the Cassowary algorithm , developed in part by Monash researchers. While constraint-based layout is powerful, it can be difficult for users to understand the interactions and behaviour
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designing and implementing new algorithms to produce visual aids to assist people to reason with causal Bayesian networks, as well as the planning and conduct of exploratory usability studies to assess
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guarantee that what one believes to be one’s secrets will remain secret. Namely, a DP algorithm cannot ensure that private attributes cannot be inferred from publicly observable attributes if they have strong
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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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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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Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats
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will provide new models and algorithms for energy-transport integration, advancing the knowledge of mitigation strategies for sustainable urban development. #sustainability PhD student role description
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environment. The virtual world runs a little like a computer game, except there are no human players, all the components of the game are computer-controlled by algorithms parameterised from real insect