Papers with Code - Dictionary Learning
**Dictionary Learning** is an important problem in multiple areas, ranging from computational neuroscience, machine learning, to computer vision and image processing. The general goal is to find a good basis for given data. More formally, in the Dictionary Learning problem, also known as sparse coding, we are given samples of a random vector $y\in\mathbb{R}^n$, of the form $y=Ax$ where $A$ is some unknown matrix in $\mathbb{R}^{n×m}$, called dictionary, and $x$ is sampled from an unknown distribution over sparse vectors. The goal is to approximately recover the dictionary $A$. <span class="description-source">Source: [Polynomial-time tensor decompositions with sum-of-squares ](https://arxiv.org/abs/1610.01980)</span>
https://paperswithcode.com/task/dictionary-learning
