1. Data that can be represented or approximated by a matrix or tensor with a low rank, typically used in machine learning and data compression to identify underlying patterns with fewer dimensions than the original dataset
Low-rank data approximation is useful for reducing computational complexity in large datasets.
A aproximação de dados de baixo posto é útil para reduzir a complexidade computacional em grandes conjuntos de dados.
2. In linear algebra, data whose intrinsic dimensionality is significantly smaller than the ambient dimensionality, allowing for efficient storage and processing
The algorithm exploits the low-rank data structure to improve performance.
O algoritmo explora a estrutura de dados de baixo posto para melhorar o desempenho.