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This work presents a geometrical analysis of the Large Step Gradient Descent (LGD) dictionary learning algorithm. LGD updates the atoms of the dictionary using a gradient step with a step size equal to twice the optimal step size. We show that the large step gradient descent can be understood as a maximal exploration step where one goes as far away as possible without increasing the error. We also...
This article deals with learning dictionaries for sparse approximation whose atoms are both adapted to a training set of signals and mutually incoherent. To meet this objective, we employ a dictionary learning scheme consisting of sparse approximation followed by dictionary update and we add to the latter a decorrelation step in order to reach a target mutual coherence level. This step is accomplished...
Although researchers are increasingly aware of the need to publish and maintain software code alongside their results, practical barriers prevent this from happening in many cases. We examine these barriers, propose an incremental approach to overcoming some of them, and describe the Sound Software project, an effort to support software development practice in the UK audio and music research community...
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