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Seminar on Intelligent Information. Fall 2014. Topic to be covered. Bayesian Networks Graphical Models and Inference Method Sampling for inference Expectation Maximization Topic Modelling using Nonpaprametric Bayesian Models LDA ….. Deep Learning Kernel Based Methods
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Seminar on Intelligent Information Fall 2014
Topic to be covered • Bayesian Networks • Graphical Modelsand Inference Method • Sampling for inference • Expectation Maximization • Topic Modelling using Nonpaprametric Bayesian Models • LDA ….. • Deep Learning • Kernel Based Methods • Semi-supervised Learning • Manifold Learning • Advanced Topics of Clustering
How to proceed the class • Lecture by lecturer or video • Basic Conceptsof Text Levels • Tools for Applications • Seminar • Group of Special Interests • Bayesian Networks • Application of Markov Random Field • LDA for document topic modelling • Topic modelling applications … • HMM and its application
How to proceed the class • Seminar • Group of Special Interests • Kernel Method/Manifold Learning/Semi-supervised learning • Kernel SVM • Spectral Clustering … • Deep Learning • Models and Types of Deep Learning • Tools for learning • How to use the tools with specific applications
How to proceed the class • Evaluation • Seminar 40 % • Term Projects 40 % • Present 20 %