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The top documents tagged [lower dimensional space]

Kohonen self organizing maps
Kohonen self organizing maps
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Accurate Face Recognition Using PCA and LDA 2
Accurate Face Recognition Using PCA and LDA 2
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Dimension reduction (1) Overview PCA Factor Analysis EDR space SIR References: Applied Multivariate Analysis. kcli/sir-PHD.pdf
Dimension reduction (1) Overview PCA Factor Analysis EDR space SIR References: Applied Multivariate Analysis. kcli/sir-PHD.pdf
221 views
Jan Kamenický. Many features ⇒ many dimensions Dimensionality reduction ◦ Feature extraction (useful representation) ◦ Classification ◦ Visualization
Jan Kamenický. Many features ⇒ many dimensions Dimensionality reduction ◦ Feature extraction (useful representation) ◦ Classification ◦ Visualization
234 views
Principal component regression When simple linear model fails Ridge regression Lasso Principal component analysis Principal component regression
Principal component regression When simple linear model fails Ridge regression Lasso Principal component analysis Principal component regression
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1 CS 430 / INFO 430 Information Retrieval Lecture 11 Latent Semantic Indexing Extending the Boolean Model
1 CS 430 / INFO 430 Information Retrieval Lecture 11 Latent Semantic Indexing Extending the Boolean Model
225 views
Principal Component Analysis Barnabás Póczos University of Alberta Nov 24, 2009 B: Chapter 12 HRF: Chapter 14.5
Principal Component Analysis Barnabás Póczos University of Alberta Nov 24, 2009 B: Chapter 12 HRF: Chapter 14.5
227 views
A Bayesian Hierarchical Model for Learning Natural Scene Categories L. Fei-Fei and P. Perona. CVPR 2005 Discovering objects and their location in images
A Bayesian Hierarchical Model for Learning Natural Scene Categories L. Fei-Fei and P. Perona. CVPR 2005 Discovering objects and their location in images
216 views
Other IR Models Non-Overlapping Lists Proximal Nodes Structured Models Retrieval: Adhoc Filtering Browsing U s e r T a s k Classic Models boolean vector
Other IR Models Non-Overlapping Lists Proximal Nodes Structured Models Retrieval: Adhoc Filtering Browsing U s e r T a s k Classic Models boolean vector
298 views
1 CS 430 / INFO 430 Information Retrieval Lecture 9 Latent Semantic Indexing
1 CS 430 / INFO 430 Information Retrieval Lecture 9 Latent Semantic Indexing
227 views
1 International Conference The Many Dimension of Poverty Brasilia, Brazil – 29-31 August 2005
1 International Conference The Many Dimension of Poverty Brasilia, Brazil – 29-31 August 2005
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Homework Define a loss function that compares two matrices (say mean square error) b = svd(bellcore) b2 = b$u[,1:2] %*% diag(b$d[1:2]) %*% t(b$v[,1:2])
Homework Define a loss function that compares two matrices (say mean square error) b = svd(bellcore) b2 = b$u[,1:2] %*% diag(b$d[1:2]) %*% t(b$v[,1:2])
221 views