Pages that link to "Item:Q676433"
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The following pages link to Neural networks with quadratic VC dimension (Q676433):
Displaying 18 items.
- Polynomial bounds for VC dimension of sigmoidal and general Pfaffian neural networks (Q676431) (← links)
- On neural network design. I: Using the MVQ algorithm (Q1126902) (← links)
- Vapnik-Chervonenkis dimension of recurrent neural networks (Q1265745) (← links)
- On the complexity of learning for spiking neurons with temporal coding. (Q1854302) (← links)
- Relation between weight size and degree of over-fitting in neural network regression (Q1931976) (← links)
- On the sample complexity for nonoverlapping neural networks (Q1964680) (← links)
- Neurodynamical classifiers with low model complexity (Q2057774) (← links)
- The Vapnik-Chervonenkis dimension of graph and recursive neural networks (Q2182896) (← links)
- On the stability and generalization of neural networks with VC dimension and fuzzy feature encoders (Q2235467) (← links)
- On the complexity of computing and learning with multiplicative neural networks (Q2780854) (← links)
- Theory of Classification: a Survey of Some Recent Advances (Q3373749) (← links)
- The Exact VC Dimension of the WiSARD n-Tuple Classifier (Q3379582) (← links)
- VC dimension of neural networks (Q4250971) (← links)
- Neural Nets with Superlinear VC-Dimension (Q4323332) (← links)
- Neural Networks with Local Receptive Fields and Superlinear VC Dimension (Q4330677) (← links)
- On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach (Q4673536) (← links)
- Descartes' Rule of Signs for Radial Basis Function Neural Networks (Q4815047) (← links)
- Neural Quadratic Discriminant Analysis: Nonlinear Decoding with V1-Like Computation (Q5380584) (← links)
