2025
IJCAI
IJCAI 2025
A Formal Theory of Optimal Learning with Experimental Results
Abstract
Here I summarise some results from my thesis which are relevant to artificial intelligence (AI) and machine learning (ML). The key contribution is a theory of optimally sample and energy efficient learning, which is supported by mathematical proofs and experimental results.
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics