Abstract
We give a bound on the expected reconstruction error for a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The result can be specialized to K-means clustering, nonnegative matrix factorization and the sparse coding techniques introduced by Olshausen and Field. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Maurer, A., & Pontil, M. (2008). Generalization bounds for K-dimensional coding schemes in Hilbert spaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5254 LNAI, pp. 79–91). https://doi.org/10.1007/978-3-540-87987-9_11
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