Date & time
Tuesday, April 24, 2018
12:30 p.m. – 1:30 p.m.
12:30 p.m. – 1:30 p.m.
Workshops & seminars
Share this event:
Digital Futures - Yoshua Bengio
Concordia President's Speaker Series on Digital Futures
Speaker(s)
Yoshua Bengio, educator, researcher, world-leader on deep learning
Cost
This event is free
Organization
Contact
Where
Henry F. Hall Building
1455 De Maisonneuve W.
Room H-110, SGW University Alumni Auditorium
Wheel chair accessible
Yes
Concordia University is developing a digital strategy. This is just one of the transformational projects being under undertaken in 2017-18 as part of the Strategic Directions initiative to position Concordia as a next-generation university.
To engage faculty, staff and students in this process, we are bringing a diverse group of thought-leaders to the university as part of the Concordia President’s Speaker Series on Digital Futures. They will share their experience and insights to spark conversations and reflections as we work together to develop a shared vision for Concordia's digital future.
NOTE: We've moved this event to a larger venue in the Henry F. Hall Building, Room H-110, the Sir George Williams University Alumni Auditorium due to demand. This event is open to the public and there is no charge.
About Yoshua Bengio
Yoshua Bengio is the world-leader and expert on deep learning and author of the bestselling book on that topic.
He is also a full professor in the Department of Computer Science and Operations at Université de Montréal, head of the Montreal Institute for Learning Algorithms (MILA), program co-director of the Canadian Institute for Advanced Research program on Learning in Machines and Brains Research Chair in Statistical Learning Algorithms of Canada and an Officer of the Order of Canada.
His research objective is to understand the mathematical and computational principles, which give rise to intelligence through learning. He contributes to a wide spectrum of machine learning areas and is well known for his theoretical results on recurrent neural networks, kernel machines, distributed representations, depth of neural architectures, and the optimization challenge of deep learning.
His work was crucial in advancing how deep networks are trained, how neural networks can learn vector embeddings for words, how to perform machine translation with deep learning by taking advantage of an attention mechanism, and how to perform unsupervised learning with deep generative models.
The author of three books and more than 300 publications, Bengio is among the most cited Canadian computer scientists and is, or has been, associate editor of the top journals in machine learning and neural networks.