This github page entails the sequential and parallel optimization of the dictionary learning algorithm ITKrM, as defined by Karin Schnass.

Her document is called Convergence radius and sample complexity of ITKrM algorithms for dictionary learning.

It was featured in Applied and Computational Harmonic Analysis, 2016. ISSN 1063-5203. doi: 10.1016/j.acha.2016.08.002.

The files within code are all the code files made through out the project, rather messy at the moment.

The files within project_code are all the code files used for testing throughout the project, cleaner, though very specific code.

MIT License

Copyright (c) [2018] [Amalie Vistoft Petersen, Jacob Theilgaard Lassen, Niels Rymann Munthe, Sebastian Biegel Schiøler]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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