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| ~~NOTOC~~ | ~~NOTOC~~ | ||
| - | ====== | + | ====== |
| ===== Description | ===== Description | ||
| - | The course | + | The course |
| + | * Bayesian Decision theory, Generative vs Discriminative modeling | ||
| + | * Generative Models - multivariate Gaussian, Gaussian mixture model (GMM), hidden Markov model (HMM), Multinomial, | ||
| + | * Discriminative Models - linear discriminant, | ||
| + | * Statistical Modeling Methods - maximum likelihood estimation (MLE), Expectation-Maximization (EM), discriminative training (DT) | ||
| + | * Some selected applications - speech recognition, | ||
| + | |||
| + | The above methods are equally applicable to other research areas, such as data mining, information retrieval, computer vision, computational linguistics and so on. | ||
| + | |||
| + | ===== Announcements ===== | ||
| + | |||
| + | * Check the left tab [[: | ||
| ===== Lecture Times ===== | ===== Lecture Times ===== | ||
| - | * Section A: Mondays and Fridays, 11:00am - 12: | + | * Section A: Mondays and Wednesdays, 11:30am - 1: |
| + | |||
| + | ===== Lecturer ===== | ||
| + | * Prof. [[http:// | ||
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