67 citations · 292 across the 17 of their papers we have counts for
5 papers · 1 filter
Entropy of Overcomplete Kernel Dictionaries
Paul Honeine
In signal analysis and synthesis, linear approximation theory considers a linear decomposition of any given signal in a set of atoms, collected into a so-called dictionary. Relevan…
Approximation errors of online sparsification criteria
Paul Honeine
Many machine learning frameworks, such as resource-allocating networks, kernel-based methods, Gaussian processes, and radial-basis-function networks, require a sparsification schem…
Analyzing sparse dictionaries for online learning with kernels
Paul Honeine
Many signal processing and machine learning methods share essentially the same linear-in-the-parameter model, with as many parameters as available samples as in kernel-based machin…
An eigenanalysis of data centering in machine learning
Paul Honeine
Many pattern recognition methods rely on statistical information from centered data, with the eigenanalysis of an empirical central moment, such as the covariance matrix in princip…
Kernel Nonnegative Matrix Factorization Without the Curse of the Pre-image - Application to Unmixing Hyperspectral Images
Fei Zhu, Paul Honeine, Maya Kallas
The nonnegative matrix factorization (NMF) is widely used in signal and image processing, including bio-informatics, blind source separation and hyperspectral image analysis in rem…