About the CIFAR Deep Learning + Reinforcement Learning School
Since 2005, when CIFAR’s Learning in Machines & Brains program hosted its first Deep Learning + Reinforcement Learning (DLRL) Summer School in Toronto, Ontario, Canada, a thriving community of DLRL Summer School graduates has grown year-over-year, with our alumni now leading some of the world’s top tech firms and university labs.
Today DLRL is a keystone next-generation offering of the CIFAR Learning in Machines & Brains program and the CIFAR Pan-Canadian AI Strategy’s AI4Good Training Program, hosted each year in partnership with Canada’s three national AI institutes: Amii in Edmonton, Mila in Montreal and the Vector Institute in Toronto.
Now in its 18th year, DLRL truly is where the world comes to learn AI.
Deep Learning (DL) Summer School
Deep neural networks are a powerful method for automatically learning distributed representations at multiple levels of abstraction. Over the past decade, they have dramatically pushed forward the state-of-the-art in domains as diverse as vision, language understanding, robotics, game playing, graphics, health care, and genomics. The DL Summer School will cover both the foundations and applications of deep neural networks, from fundamental concepts to leading-edge research results.
Reinforcement Learning (RL) Summer School
Reinforcement Learning is a family of approaches for developing systems that learn optimal behaviour through interaction with an environment. In recent years, reinforcement learning has seen success as an essential component of Deep Reinforcement Learning, which has helped AI researchers achieve previously unheard of results in games like Go and in the development of autonomous vehicles. The RL Summer School will cover the basics of reinforcement learning and show its most recent research trends and discoveries, as well as present an opportunity to interact with graduate students and senior researchers in the field.