Dictionary learning

Dictionary learning is a machine learning technique that aims to find a set of basic building blocks, called "atoms," to efficiently represent complex data such as images or signals. By combining these atoms in various ways, the original data can be reconstructed accurately. Think of it like creating a customized vocabulary: instead of using entire sentences, you break down information into basic words (atoms) that, when combined, express the full message. This approach helps in data compression, noise reduction, and feature extraction, making it easier to analyze and interpret complex datasets.