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Events Archive

Seminar: Stochastic Gradient and Mirror Descent: Minimax Optimality and Implicit Regularization

Abstract: Stochastic descent methods (of the gradient and mirror varieties) have become increasingly popular in optimization.

Location: B205 Engineering Quadrangle
Speaker(s):

Fundamentals of Deep Learning for Computer Vision with NVIDIA

This workshop teaches you to apply deep learning techniques to a range of computer vision tasks through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows to train and deploy neural network models on a fully-configured, GPU accelerated workstation in the cloud.

Location: PCTS, 407 Jadwin Hall

Seminar: Latent statistical structure in large-scale neural data: how to find it, and when to believe it

One central challenge in neuroscience is to understand how neural populations represent and produce the remarkable computational abilities of our brains.  Indeed, neuroscientists increasingly form scientific hypotheses that can only be studied at the level of the neural population, and exciting new large-scale datasets have followed. ...

Location: Friend Center, Room 006

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