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Data, Environments, and Learners: Theory and Algorithms
Research Group at UCL Statistical Science
Led by Omar Rivasplata
IMSS Fellow
Top-level areas of interest
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Algorithmic Learning Theory.   Machine Learning Theory and Practice.   Probability and Statistics.  
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What is this research group about? |
The group's mission is producing meaningful knowledge about machine learning algorithms.
We are interested in sound theory that helps to understand the performance (optimisation, generalisation) of machine learning algorithms, most notably (but not only) deep learning algorithms which are highly relevant nowadays since neural networks are important components of many modern algorithmic learning systems, aka AI.
We aim to develop learning and certification strategies that make efficient use of the available data and deliver reliable performance guarantees.
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Probability Links (probably accessible) |
Stats Links (most significant) |
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