PCA

A Tutorial on Principal Component Analysis

• arxiv: http://arxiv.org/abs/1404.1100

Compressive PCA on Graphs

• arxiv: http://arxiv.org/abs/1602.02070

Robust Principal Component Analysis on Graphs

• arxiv: http://arxiv.org/abs/1504.06151
• project: https://lts2.epfl.ch/blog/nauman/recent-projects/
• code: http://pan.baidu.com/s/1gepgIUv

Fast Randomized PCA/SVD

• blog: https://research.facebook.com/blog/294071574113354/fast-randomized-svd/
• baidu-pan: http://pan.baidu.com/s/1nt8I8qt
• github: https://github.com/facebook/fbpca

Improper applications of Principal Component Analysis on multimodal data

• blog: http://nxn.se/post/117471851320/improper-applications-of-principal-component

Principal Component Analysis

• blog: http://setosa.io/ev/principal-component-analysis/
• homepage(“Explained Visually”): http://setosa.io/ev/

Fast Algorithms for Robust PCA via Gradient Descent

• arxiv: http://arxiv.org/abs/1605.07784
• code: https://people.orie.cornell.edu/yudong.chen/rpca_gd/RPCA_GD.zip

Coherence Pursuit: Fast, Simple, and Robust Principal Component Analysis

• arxiv: https://arxiv.org/abs/1609.04789

A Fast Factorization-based Approach to Robust PCA

• arxiv: https://arxiv.org/abs/1609.08677

PCA Tutorial

• blog: http://www.danvatterott.com/blog/2016/11/06/pca-tutorial/

SVD

Feature Reduction using SVD

• blog: http://blog.applied.ai/feature-reduction-using-svd/
• ipn: http://nbviewer.jupyter.org/urls/bitbucket.org/appliedai/appliedai_svd/raw/02901de3aaa01be7b4536f484401113ddd5da8a9/01_FeatureReduction.ipynb

data-projector: Visualizing High-Dimensional Data in the Browser with SVD, t-SNE and Three.js

• github: https://github.com/datacratic/data-projector
• blog: http://datacratic.com/site/blog/visualizing-high-dimensional-data-browser-svd-t-sne-and-threejs
• demo: http://opensource.datacratic.com/data-projector/

RedSVD

• code: https://code.google.com/p/redsvd/
• github: https://github.com/handong1587/redsvd
• github: https://github.com/ntessore/redsvd-h

OpenCV 3.1.0: cv::SVD Class Reference

http://docs.opencv.org/3.1.0/df/df7/classcv_1_1SVD.html#gsc.tab=0

Singular Value Decomposition Part 1: Perspectives on Linear Algebra

• blog: https://jeremykun.com/2016/04/18/singular-value-decomposition-part-1-perspectives-on-linear-algebra/

Even Faster SVD Decomposition Yet Without Agonizing Pain

• arxiv: http://arxiv.org/abs/1607.03463

ICA

Independent component analysis

• blog: http://efavdb.com/independent-component-analysis/
• ipython notebook: http://nbviewer.jupyter.org/github/EFavDB/ICA/blob/master/pyaudio.ipynb

Projects

Decomposition module for Torch7: Component Analysis using Torch7 (PCA, Whitened PCA, LDA, LPP, NPP, FastICA)

• github: https://github.com/iassael/torch-decomposition

Resources

Linear Dimensionality Reduction

• instructor: Percy Liang. CS294-10
• slides: http://vis.lbl.gov/~romano/mlgroup/papers/linear-dim-red.pdf

Readings and Questions

• reddit: https://www.reddit.com/r/MachineLearning/comments/4dkxm3/what_is_better_pca_or_svd/