Translator Disclaimer
Paper
24 August 2015 Learning Boolean functions with concentrated spectra
Author Affiliations +
Abstract
This paper discusses the theory and application of learning Boolean functions that are concentrated in the Fourier domain. We first estimate the VC dimension of this function class in order to establish a small sample complexity of learning in this case. Next, we propose a computationally efficient method of empirical risk minimization, and we apply this method to the MNIST database of handwritten digits. These results demonstrate the effectiveness of our model for modern classification tasks. We conclude with a list of open problems for future investigation.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dustin G. Mixon and Jesse Peterson "Learning Boolean functions with concentrated spectra", Proc. SPIE 9597, Wavelets and Sparsity XVI, 95970C (24 August 2015); https://doi.org/10.1117/12.2189112
PROCEEDINGS
8 PAGES


SHARE
Advertisement
Advertisement
Back to Top