Radial Basis Function Neural Networks Have Superlinear VC Dimension
| Authored By: | Michael Schmitt |
| Paper Title: | Radial Basis Function Neural Networks Have Superlinear VC Dimension |
| Book/Journal Title: | 14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, July 2001, Proceedings |
| Vol. 2111 | |
| Publisher: | Springer |
| Publication Date: | 2001 |
| Pages: | 14-30 |
BibTeX Record:
@InProceedings{s-rbfnnhs-01,
title = "Radial Basis Function Neural Networks Have Superlinear {VC} Dimension",
author = "Michael Schmitt",
booktitle = "14th Annual Conference on Computational Learning Theory, {COLT} 2001 and 5th {E}uropean Conference on Computational Learning Theory, {EuroCOLT} 2001, Amsterdam, The Netherlands, July 2001, Proceedings",
series = "Lecture Notes in Artificial Intelligence",
volume = "2111",
publisher = "Springer",
year = "2001",
pages = "14--30",
}
Hide BibTeX Record
@InProceedings{s-rbfnnhs-01,
title = "Radial Basis Function Neural Networks Have Superlinear {VC} Dimension",
author = "Michael Schmitt",
booktitle = "14th Annual Conference on Computational Learning Theory, {COLT} 2001 and 5th {E}uropean Conference on Computational Learning Theory, {EuroCOLT} 2001, Amsterdam, The Netherlands, July 2001, Proceedings",
series = "Lecture Notes in Artificial Intelligence",
volume = "2111",
publisher = "Springer",
year = "2001",
pages = "14--30",
}