Machine Learning for Graphics, Vision and Multimedia

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Recently, machine learning techniques have been proven and widely used in the fields of computer graphics, computer vision and multimedia. In this course, we will study these algorithms and their applications.

Time: 2:20pm-5:20pm Thursday

Classroom:CSIE Room 111

Presentation Guidelines:

Topics

Date Topic Tutorial References
03/16 Principal Component Analysis
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PCA
03/23 PCA Extensions
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PCA missing data
Robust PCA
03/30 Isomap
Locally Linear Embedding

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ISOMAP & LLE
04/06 Laplacian Eigenmaps
Linear Discriminant Analysis
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LDA
LDA applications
04/13 Locality Preserving Projection
Local Discriminant Embedding

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LPP
04/27
05/04
Support Vector Machines
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SVM
SVM
SVM
libsvm
Support Vector Regression
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SVR
Relevance Vector Machine
RVM
05/11 Boosting
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Ensemble Learning
AdaBoost binary
AdaBoost extensions
AdaBoost applications
05/18
05/25
Graphical Models
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Graphical Model
Belief Propagation
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low-level learning
Applications
05/25
06/01
06/08
Approximate Inference
Expectation Maximization
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Variational Learning
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Variational Learning
Variational Learning
Variational Learning

Resources