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~~NOTOC~~ | ~~NOTOC~~ | ||
- | ====== | + | ====== |
===== Description | ===== Description | ||
- | The course | + | The course |
+ | * Bayesian Decision theory, Generative vs Discriminative modelling | ||
+ | * Generative Models (1) - multivariate Gaussian, Gaussian mixture model (GMM), | ||
+ | * Generative Models (2) - graphical models, directed vs. indirected graphical models, exact inference, approximate inference (loopy belief propagation, variational inference, Monte Carlo methods) | ||
+ | * Discriminative Models (1) - linear discriminant, | ||
+ | * Discriminative Models (2) - neural networks (NN), back-propagation, | ||
+ | * Advanced models: hidden Markov model (HMM), | ||
+ | * Advanced topics: Learnability, Gaussian Processes, Ensemble Methods, Reinforcement Learning, etc. | ||
+ | |||
+ | |||
+ | ===== Announcements ===== | ||
+ | |||
+ | * Check the left tab [[: | ||
===== Lecture Times ===== | ===== Lecture Times ===== | ||
- | * Section A: Mondays | + | * Section A: Wednesdays |
+ | 204</ | ||
+ | |||
+ | ===== Lecturer ===== | ||
+ | * Prof. [[http:// |
start.1187105762.txt.gz · Last modified: 2012/08/30 18:37 (external edit)