The Logic & Learning School is an opportunity to learn from, and interact with, the world's experts leading recent progress in understanding
the relationships between logic and learning. These experts come from both academia and some of the leading industrial research labs
(Amazon Research and DeepMind).
In the last few decades, logic has emerged as a fundamental paradigm for understanding complex systems. It has turned out to be instrumental in formal methods such as program verification, reasoning about hardware, reasoning about real-time systems and, more recently, probabilistic systems. Machine learning has recently had spectacular successes in fields such as image recognition, game playing, and many areas that involve the extraction of information from large datasets. The use of statistical approaches yields practical solutions to problems that seemed out of reach just a few years ago. The understanding of why these approaches are so successful has lagged behind the empirical successes. Using logic as the foundation to understand machine learning to obtain the best of both worlds is a major challenge.
The programme of the Logic & Learning School consists in eleven lectures of three hours each, starting with five introductory courses on computational and statistical learning theory, reinforcement learning, Bayesian inference, and automata learning, and six advanced courses on exciting and recent developments relating logic and learning. The lectures target an audience of logicians and computer scientists broadly construed and do not assume any knowledge on machine learning. Accordingly, the School represents a perfect opportunity to learn for both students and working researchers. The School will take place in St Anne's College in the centre of Oxford, an ideal learning environment with accommodation and lunches provided on site (see local information).
The lectures will be from Sunday 1st July in the morning to Friday 6 July in the afternoon, which is the week before the main activities of FLoC.
