Hallmarks of Deep Learning in the Brain

Hallmarks of Deep Learning in the Brain Seminar | February 17 | 2-3:30 p.m. | 560 Evans Hall Speaker/Performer: Andrew Saxe, Harvard Sponsor: Neuroscience Institute, Helen Wills Anatomically, the brain is deep. To understand the ramifications of depth on learning in the brain requires a clear theory of deep learning. I develop the theory of gradient descent learning in deep linear neural networks, which gives exact quantitative answers to fundamental questions such as how learning speed scales with depth, how unsupervised pretraining speeds learning, and how internal representations change across a deep network. Several key hallmarks of deep learning are consistent with behavioral and neural observations. The theory can be further specialized for specific experimental paradigms. Taking visual perceptual learning as an example, I show that a deep learning theory accounts for…

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