Credit points: 3.0
Neural networks as computation models. The perception. Separability of data points. Realization of Boolean functions by multi-layer networks. Classification.The generalization problem. Approximating continuous functions by neural networks. Learning and data storage methods.Density function estimation. Bayesian methods. Regularization. Associative memories: storage capacity and dynamics of fully and partially connected networks.
Neural networks as computation models. The perception. Separability of data points. Realization of Boolean functions by multi-layer networks. Classification.The generalization problem. Approximating continuous functions by neural networks. Learning and data storage methods.Density function estimation. Bayesian methods. Regularization. Associative memories: storage capacity and dynamics of fully and partially connected networks.