sparse-coding

Sparse coding is an approach in signal processing and machine learning where data is represented as a linear combination of a small number of basis functions, leading to a more compact representation. This method is particularly effective in scenarios involving high-dimensional data, as it can enhance interpretability and reduce computational complexity. Applications include image processing and feature extraction.