Deep Learning and Reinforcement Learning Summer School 2019

July 24 – August 2, 2019

Edmonton, Alberta
Canada

About

Deep Learning Summer School (DLSS)

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 DLSS will cover both the foundations and applications of deep neural networks, from fundamental concepts to leading-edge research results.

DLSS is aimed at graduate students, postdocs, and industry professionals who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.

Reinforcement Learning Summer School (RLSS)

The RLSS 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.

RLSS is intended for graduate students in Machine Learning and related fields. Participants should have advanced prior training in computer science and mathematics.

Stay tuned for information about speakers, schedule, registration, fees, and recommended parking and accommodation options. To receive updates as they come, please sign up for our newsletter:

DLRL 2018

Deep Learning and Reinforcement Learning Summer School 2018 was hosted by the Vector Institute and took place from July 25 to August 3 in Toronto, Ontario.

The 2019 DLSS and the RLSS are hosted by the Canadian Institute For Advanced Research (CIFAR) and the Alberta Machine Intelligence Institute, with participation and support from the Vector Institute and the Institut québécois d’intelligence artificielle (MILA).

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