Paul J. Atzberger | Research Group
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Slides


Statistical Learning Theory, Generalization Errors, and Sampling Complexity Bounds: [PDF] [MicrosoftSlides]


Complexity Measures, Radamacher, VC-Dimension: [PDF] [MicrosoftSlides]


Support Vector Machines, Kernels, Optimization Theory Basics: [PDF] [MicrosoftSlides]


Regression, Kernel Methods, Regularization, LASSO, Tomography: [PDF] [MicrosoftSlides]


Unsupervised Learning, Dimension Reduction, Manifold Learning: [Large Slides] [PDF] [MicrosoftSlides]


Neural Networks and Deep Learning Basics: [PDF] [GoogleSlides]


Convolutional Neural Networks (CNNs) Basics: [PDF] [GoogleSlides]


Recurrent Neural Networks (RNNs) Basics: [PDF] [MicrosoftSlides]


Generative Adversarial Networks (GANs): [PDF] [MicrosoftSlides]


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