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ONMF_ONTF_NDL

Online Nonnegative Matrix/Tensor Factorization algorithms with applications in dictionary learning for image and network data.

For network dictionary learning experiments, we recommend to look at an alternative repository NDL_paper associated with the more recent paper

Hanbaek Lyu, Yacoub Kureh, Joshua Vendrow, and Mason A. Porter,
"Learning low-rank latent mesoscale structures in networks" (arXiv 2021)

References

These codes are based on my papers below:

  1. Hanbaek Lyu, Deanna Needell, and Laura Balzano, “Online matrix factorization for markovian data and applications to network dictionary learning.” Journal of Machine Learning Research. 21(251):1−49, 2020 (Preprint, Journal)
  2. Hanbaek Lyu, Facundo Memoli, and David Sivakoff, “Sampling random graph homomorphisms and applications to network data analysis.” https://arxiv.org/abs/1910.09483

File description

  1. onmf.py : Online Nonnegative Matrix Factorization algorithm
  2. ontf.py : Online Nonnegative Tensor Factorization algorithm (Matricization + ONMF. For a proper CP-decomposition, see OCPDL)
  3. image_reconstruction.py : Dictionary learning / Image reconstruction based on onmf.py
  4. image_reconstruction_tensor.py : Dictionary learning / reconstruction for color images based on ontf.py
  5. network_reconstruction_nx.py : Network Dictionary Learning proposed in reference [1] for networkx format
  6. ising_simulator.py : Gibbs sampler for the 2-dimensional Ising model
  7. ising_reconstruction.py : Dictionary learning / reconstruction from MCMC trajectory of Ising spin configurations

Authors

  • Hanbaek Lyu - Initial work - Website

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • My REU students Nick Hanoian and Henry Sojico for polishing up onmf.py and image_reconstruction.py

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Online Matrix/Tensor Factorization and applications to Network Dictionary Learning and images

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