Vector Quantization by Minimizing Kullback-Leibler Divergence

no code implementations • 30 Jan 2015 • Lan Yang, Jingbin Wang, Yujin Tu, Prarthana Mahapatra, Nelson Cardoso

This paper proposes a new method for vector quantization by minimizing the Kullback-Leibler Divergence between the class label distributions over the quantization inputs, which are original vectors, and the output, which is the quantization subsets of the vector set.

General Classification Image Classification +1