Haim Sompolinsky, Hebrew Univ. Israel and Harvard Univ. USA
Statistical Mechanics of Deep Neural Networks
(10.5h)
1. Learning in neural networks: architectures, algorithms, training and generalization
2. Learning in a single layer network: The perceptron and Support Vector Machines
3. Deep Recursive Networks: A minimal model of Deep Neural
Networks (DNNs)
4. Classification and geometry of neural object manifolds
5. Object manifolds in artificial and biological DNNs