Dense shattering and teaching dimensions for differentiable families (extended abstract)
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
On the Sample Complexity for Nonoverlapping Neural Networks
Machine Learning
Model complexity control and statisticallearning theory
Natural Computing: an international journal
Neural networks with local receptive fields and superlinear VC Dimension
Neural Computation
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
On the Sample Complexity for Neural Trees
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
RBF Neural Networks and Descartes' Rule of Signs
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Radial Basis Function Neural Networks Have Superlinear VC Dimension
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Descartes' rule of signs for radial basis function neural networks
Neural Computation
The VC Dimension for Mixtures of Binary Classifiers
Neural Computation
Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks
Neural Computation
MUSP'09 Proceedings of the 9th WSEAS international conference on Multimedia systems & signal processing
Designing neural networks for tackling hard classification problems
WSEAS TRANSACTIONS on SYSTEMS
Estimating the size of neural networks from the number of available training data
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Hi-index | 0.00 |