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Theories of Deep Learning
Instructor: David Donoho, Hatef Monajemi, Vardan Papyan
Department: Statistics
Institution: Stanford University
Platform: Independent
Year: 2017
Price: Free
Ian Goodfellow and Yoshua Bengio and Aaron Courville. Deep Learning. 2016.
Nielsen. Neural Networks and Deep Learning Nielsen. 2015.
The spectacular recent successes of deep learning are purely empirical. Nevertheless intellectuals always try to explain important developments theoretically. In this literature course we will review recent work of Bruna and Mallat, Mhaskar and Poggio, Papyan and Elad, Bolcskei and co-authors, Baraniuk and co-authors, and others, seeking to build theoretical frameworks deriving deep networks as consequences. After initial background lectures, we will have some of the authors presenting lectures on specific papers. This course meets once weekly.