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Dimensionality Reduction for Matrix- and Tensor-Coded Data
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- 1 Intro
- 2 Strategy
- 3 Other datasets
- 4 Imaging datasets
- 5 Matrix decomposition
- 6 Outline
- 7 Formal Definition
- 8 The Rotation Problem
- 9 NonNegative Matrix Factorization
- 10 Sparse Principal Components Analysis
- 11 L1 vs L2 penalties
- 12 Sparse PCA
- 13 Sparse NMF
- 14 Bayes Rule
- 15 Logistic PCA
- 16 Loss Functions
- 17 General Framework
- 18 Alternating minimization
- 19 In practice
- 20 Crossvalidation