Seminar 3 : Marrying Reinforcement Learning and Deep Learning

The Computer Science Graduate Society is pleased to present the first talk of the winter semester by Emmanuel Bengio on 15th January. To help us know how much food to order, please fill this Google form if you plan to attend: http://goo.gl/forms/9lVPNT5tyV

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Date: January 15
Time: 13:00-14:00
Location: McConnell Room 103

Speaker: Emmanuel Bengio
Title: Marrying Reinforcement Learning and Deep Learning

Abstract: In the last few years Machine Learning has boosted in popularity thanks to the outrageously successful applications of Deep Learning, in many areas including speech recognition, fraud detection, advertisement, recommendation systems, and, probably most famously, computer vision.
Taking advantage of these techniques, we have also very recently seen successful use of Deep Learning as a tool inside of Reinforcement Learning tasks, such as DeepMind’s popular Atari model. A new approach, which is the main concern of my research, consists in studying the opposite direction: using Reinforcement Learning to augment Deep Learning models. This takes the form of conditional computing, visual attention, memory mechanisms, and much more, which I will discuss during this talk.

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