This work contains the work done in the project Recent Advances in Machine Learning.
Here we provide a general view of the theme, implemeting in the Julia language 3 papers:
K-SVD: https://sites.fas.harvard.edu/~cs278/papers/ksvd.pdf (Based on the implementation of Ishita Takeshi).
GDDL (Greedy Deep Dictionary Learning) : https://arxiv.org/pdf/1602.00203.pdf
Online Dictionary Learning for Sparse Coding: https://www.di.ens.fr/sierra/pdfs/icml09.pdf
Each paper is implemented in a different Jupyter Notebook, so that you can test them.
We have used for our experiments the MNIST dataset and the CIFAR dataset:
K-SVD (Task: Compression, MNIST):
Original:
Reconstructed (95% of sparsity):
GDDL (Task: Interpretability,MNIST):
Layers of the encoder:
Online Dictionary Learning for Sparse Coding (Task: Compression,CIFAR)
Original:
Reconstructed (95% of sparsity):
