Prediction on Spike Data Using Kernel Algorithms
Abstract
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orienta- tion of visual stimuli from the activity of a population of simultaneously recorded neurons. We compare several ways of improving the coding of the input (i.e., the spike data) as well as of the output (i.e., the orienta- tion), and report the results obtained using different kernel algorithms.
Cite
Text
Eichhorn et al. "Prediction on Spike Data Using Kernel Algorithms." Neural Information Processing Systems, 2003.Markdown
[Eichhorn et al. "Prediction on Spike Data Using Kernel Algorithms." Neural Information Processing Systems, 2003.](https://mlanthology.org/neurips/2003/eichhorn2003neurips-prediction/)BibTeX
@inproceedings{eichhorn2003neurips-prediction,
title = {{Prediction on Spike Data Using Kernel Algorithms}},
author = {Eichhorn, Jan and Tolias, Andreas and Zien, Alexander and Kuss, Malte and Weston, Jason and Logothetis, Nikos and Schölkopf, Bernhard and Rasmussen, Carl E.},
booktitle = {Neural Information Processing Systems},
year = {2003},
pages = {1367-1374},
url = {https://mlanthology.org/neurips/2003/eichhorn2003neurips-prediction/}
}