As the computation power available to us continues to grow, probabilistic computing is becoming practical for increasingly large number of situations. This lecture is by Zoubin Ghahramani, elected Fellow of the Royal Society (FRS) in 2015.
His certificate of election for FRS reads as follows:
Zoubin Ghahramani is a world leader in the field of machine learning, significantly advancing the state-of-the-art in algorithms that can learn from data. He is known in particular for fundamental contributions to probabilistic modeling and Bayesian nonparametric approaches to machine learning systems, and to the development of approximate variational inference algorithms for scalable learning. He is one of the pioneers of semi-supervised learning methods, active learning algorithms, and sparse Gaussian processes. His development of novel infinite dimensional nonparametric models, such as the infinite latent feature model, has been highly influential
Enjoy the lecture!