Mathematical Finance & Financial Data Science Seminar
Speaker: Dhruv Madeka, Amazon
Location: Warren Weaver Hall 109
Date: Tuesday, November 28, 2017, 7:10 p.m.
Deep Learning usually refers to a set of computational models, composed of multiple processing layers, that perform tasks on data by generating multiple intermediate representations. These models have surpassed state of the art performance in many different tasks, and have become the focus of a vast amount of scientific literature. In this talk, we will begin by covering the basics of Deep Learning - including an overview of backpropagation, gradient descent methods, regularization, representation learning and the latest information bottleneck theories. We will also review some of the important modifications of the standard feedforward network, namely Convolutional and Recurrent architectures, and describe how they are applied in industry.
Note that this seminar will be held in room 109 (and not in the usual room).