MSc in Intelligent Systems 2007-2008 Advanced Topics in Machine Learning (part II) |
Overview In this course we will discuss linear probabilistic models for regression, Gaussian processes, linear and nonlinear dynamical systems (including sigma points filters and particle filters). We will also cover Dirichlet processes and continuous-time stochastic processes (including the basics of Ito calculus and an introduction to stochastic differential equations) . The main objective of the course is to study a number of advanced topics in Machine Learning in detail and to implement two techniques related to the topics discussed in class. Several guest speakers will also be invited to talk about their respective field of expertise. For additional details on the course, please refer to the syllabus. Unless otherwise stated, the course will take place on Fridays from 10:00 to 13:00 in room 339 of the Rockefeller building, University College London. For more information about the course or if you want to attend (and are not a MSc student), please contact Cedric Archambeau. |
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Schedule
Last updated on 07 February 2008. |