Self-awareness is a broad concept borrowed from cognitive science and psychology that describes the property of a system, which has knowledge of “itself,” based on its own senses and internal models. This knowledge may take different forms, is based on perceptions of both internal and external phenomena, and is essential for being able to anticipate… Continue reading Self-awareness for autonomous systems
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Intelligent Monitoring and Control of Interconnected Cyber-Physical Systems
The emergence of interconnected cyber-physical systems and sensor/actuator networks has given rise to advanced automation applications, where a large amount of sensor data is collected and processed in order to make suitable real-time decisions and to achieve the desired control objectives. However, in situations where some components behave abnormally or become faulty, this may lead… Continue reading Intelligent Monitoring and Control of Interconnected Cyber-Physical Systems
Real-World Learning
In the past decade, artificial intelligence has made remarkable progress, achieving feats like self-driving cars, defeating go-masters, and precise image categorisation through supervised deep learning with labelled data. However, a significant challenge is that deep learning models tend to be biased towards their training conditions and struggle in real-world situations that differ from their training… Continue reading Real-World Learning
The power of cooperation in networks of learning agents
We study the power of cooperation in a network of communicating agents that solve a learning task. Agents use an underlying communication network to get information about what the other agents know. In the talk, we show the extent to which cooperation allows to prove performance bounds that are strictly better than the known bounds… Continue reading The power of cooperation in networks of learning agents
Introduction to Tropical Geometry and its Applications to Machine Learning
Tropical geometry is a relatively recent field in mathematics and computer science combining elements of algebraic geometry and polyhedral geometry. It has recently emerged in the study of deep neural networks (DNNs) and other machine learning systems. In this talk we will first summarise introductory ideas and tools of tropical geometry and its underlying max-plus… Continue reading Introduction to Tropical Geometry and its Applications to Machine Learning
Machine learning for medicine and healthcare
Medicine stands apart from other areas where machine learning can be applied. While we have seen advances in other fields with lots of data, it is not the volume of data that makes medicine so hard, it is the challenges arising from extracting actionable information from the complexity of the data. It is these challenges… Continue reading Machine learning for medicine and healthcare