Information Processing Letters
Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
What size net gives valid generalization?
Neural Computation
Approximate matching of polygonal shapes (extended abstract)
SCG '91 Proceedings of the seventh annual symposium on Computational geometry
Machine learning: a theoretical approach
Machine learning: a theoretical approach
Computational learning theory: an introduction
Computational learning theory: an introduction
Finiteness results for sigmoidal “neural” networks
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Bounds for the computational power and learning complexity of analog neural nets
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Feedforward nets for interpolation and classification
Journal of Computer and System Sciences
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning one-dimensional geometric patterns under one-sided random misclassification noise
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Lower bounds on the VC-dimension of smoothly parametrized function classes
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
On real Turing machines that toss coins
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Sample sizes for sigmoidal neural networks
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
VC-Dimension Analysis of Object Recognition Tasks
Journal of Mathematical Imaging and Vision
Vapnik-chervonenkis generalization bounds for real valued neural networks
Neural Computation
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