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Prediction on Spike Data Using Kernel Algorithms
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation 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 orientation), and report the results obtained using different kernel algorithms.
@inproceedings{2483, title = {Prediction on Spike Data Using Kernel Algorithms}, journal = {Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference}, booktitle = {Advances in Neural Information Processing Systems 16}, abstract = {We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation 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 orientation), and report the results obtained using different kernel algorithms.}, pages = {1367-1374}, editors = {S Thrun and LK Saul and B Sch{\"o}lkopf}, publisher = {MIT Press}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Cambridge, MA, USA}, month = jun, year = {2004}, slug = {2483}, author = {Eichhorn, J. and Tolias, AS. and Zien, A. and Kuss, M. and Rasmussen, CE. and Weston, J. and Logothetis, NK. and Sch{\"o}lkopf, B.}, month_numeric = {6} }