Mathematical foundations of deep learning models and algorithms
Konstantinos Spiliopoulos
Bok · Engelsk · 2025
| Medvirkende | |
|---|---|
| Omfang | pages cm.
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| Opplysninger | Linear regression -- Logistic regression -- From perceptron to kernels to neural networks -- Feed forward neural networks -- Backpropagation -- Basics on stochastic gradient descent -- Stochastic gradient descent for multi-layer networks -- Regularization and dropout -- Batch normalization -- Training, validation, and testing -- Feature importance -- Recurrent neural networks and sequential data -- Convolution neural networks -- Variational inference and generative models -- Universal approximation theorems -- Convergence analysis of gradient descent -- Convergence analysis of stochastic gradient descent -- The neural tangent kernel regime -- Optimization in feature learning regime : mean field scaling -- Reinforcement learning -- Neural differential equations -- Distributed training -- Automatic differentiation.
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| Emner | |
| ISBN | 9781470481087. - 9781470483999
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| ISBN(galt) |