Sparse Representation

Sparse representation describes data with a representation in which only a limited number of elements are non-zero or active. Instead of storing or processing every possible feature, a model focuses on the features that contribute most to the representation. This approach can improve efficiency and reduce the amount of data that needs to be processed.

Sparse representation can reduce computational and storage requirements while preserving important information. It can also make certain machine learning models more efficient and interpretable, particularly when working with high-dimensional datasets containing many irrelevant or redundant features.