Quantum data compression by principal component analysis

22 Nov 2018 Yu Chao-Hua Gao Fei Lin Song Wang Jingbo

Data compression can be achieved by reducing the dimensionality of high-dimensional but approximately low-rank datasets, which may in fact be described by the variation of a much smaller number of parameters. It often serves as a preprocessing step to surmount the curse of dimensionality and to gain efficiency, and thus it plays an important role in machine learning and data mining... (read more)

PDF Abstract
No code implementations yet. Submit your code now

Categories


  • QUANTUM PHYSICS