UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

K-Dimensional Coding Schemes in Hilbert Spaces

Maurer, A; Pontil, M; (2010) K-Dimensional Coding Schemes in Hilbert Spaces. IEEE T INFORM THEORY , 56 (11) 5839 - 5846. 10.1109/TIT.2010.2069250.

Full text not available from this repository.


This paper presents a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The method is based on empirical risk minimization within a certain class of linear operators, which map the set of coding vectors to the Hilbert space. Two results bounding the expected reconstruction error of the method are derived, which highlight the role played by the codebook and the class of linear operators. The results are specialized to some cases of practical importance, including K-means clustering, nonnegative matrix factorization and other sparse coding methods.

Title:K-Dimensional Coding Schemes in Hilbert Spaces
Keywords:Empirical risk minimization, estimation bounds, K-means clustering and vector quantization, statistical learning, NONNEGATIVE MATRIX FACTORIZATION, GENERALIZATION ERROR, QUANTIZER DESIGN
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

Archive Staff Only: edit this record