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# # Additional Reading
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# ## Hierarchical clustering
#
# - [Hierarchical clustering wikipedia](https://en.wikipedia.org/wiki/Hierarchical_clustering)
# - [fastcluster paper](papers/fasctluster.pdf)
#     - Recent paper that reimplements several clustering methods, much faster than before
#
# ## Matrix decomposition
#
# - [Presentation on PCA](papers/wood_pca_2009.pdf)
#     - Presentation with nice examples
# - [PCA vs ICA](papers/pca_vs_ica_2009.pdf)
#     - Explains math behind PCA and ICA and compares on faces dataset
#
# ## Manifold learning
#
# - [MDS Wikipedia](https://en.wikipedia.org/wiki/Multidimensional_scaling)
# - [t-SNE paper](https://lvdmaaten.github.io/publications/papers/JMLR_2008.pdf)
#     - Really excellent paper that explains not only t-SNE but other embedding algorithms as well, using the digits, faces, and other datasets.
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