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start [2012/09/01 03:16] – hj | start [2019/09/04 16:12] (current) – hj | ||
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~~NOTOC~~ | ~~NOTOC~~ | ||
- | ====== | + | ====== |
===== Description | ===== Description | ||
- | The course introduces some basic statistical modeling methods in pattern recognition | + | The course introduces some probabilistic models |
- | * Bayesian Decision theory, Generative vs Discriminative | + | * Bayesian Decision theory, Generative vs Discriminative |
- | * Generative Models - multivariate Gaussian, Gaussian mixture model (GMM), | + | * Generative Models |
- | * Discriminative Models - linear discriminant, | + | * Generative Models (2) - graphical models, directed vs. indirected |
- | * Statistical Modeling Methods - maximum likelihood estimation | + | * Discriminative Models |
- | * Some selected applications - speech recognition, text categorization, machine translation, spoken language processing | + | * Discriminative Models (2) - neural networks (NN), |
+ | * Advanced models: hidden Markov model (HMM), | ||
+ | * Advanced topics: Learnability, Gaussian Processes, Ensemble Methods, Reinforcement Learning, etc. | ||
- | The above methods are equally applicable to other research areas, such as data mining, information retrieval, computer vision, computational linguistics and so on. | ||
===== Announcements ===== | ===== Announcements ===== | ||
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===== Lecture Times ===== | ===== Lecture Times ===== | ||
- | * Section A: Mondays and Wednesdays, | + | * Section A: Mondays and Wednesdays, |
===== Lecturer ===== | ===== Lecturer ===== | ||
* Prof. [[http:// | * Prof. [[http:// |
start.1346469373.txt.gz · Last modified: 2012/09/01 03:16 by hj