21 July 2019
In the seminar Machine Learning the following topics will be covered:
• A short introduction to the general state of the art in Machine Learning
• The perceptron and related models (e.g. multi-layers feed-forward nets)
• An introduction to stochastic dynamics
• A general theory for constructing learning rules
• The (restricted) Boltzmann machine learning and its equivalence to Hebbian learning
All of these topics can be found in the book Theory of Neural information Processing Systems, by A.C.C. Coolen, R. Khuen, P. Sollich. The participants of the seminar are recommended to obtain a copy of this book prior to participating.
ELENA AGLIARI, SAPIENZA UNIVERSITY
Advanced undergraduates and graduate students or even faculty majored in Mathematics, Physics, Computer Science, Electrical Engineering, Bioengineering, or Neuroscience.
USD 1500: Includes room and board as well as excursions
Extensive range of scholarships and discounts for registrations in more than one seminar (see our Tuition and Registration page)