Master Class: Deep Learning of Representations

SpeakerYoshua Bengio
AffiliationDepartment of Computer Science and Operations Research, University of Montreal
DateMonday, 21 Oct 2013
Time13:00 - 14:00
LocationGalton Lecture Theatre, 1-19 Torrington Place
Event seriesMaster Class: Yoshua Bengio (21 Oct - 24 Oct 2013)

Deep learning methods have been extremely successful recently, in particular in the areas of speech recognition, object recognition and language modeling. Deep representations are representations at multiple levels of abstraction, of increasing non-linearity. The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more or less the different explanatory factors of variation behind the data. Although specific domain knowledge can be used to help design representations, learning with generic priors can also be used, and the quest for AI is motivating the design of more powerful representation-learning algorithms implementing such priors. This talk introduces basic concepts in representation learning, distributed representations, and deep learning, both supervised and unsupervised.

The video recording of this masterclass is available here:
Oct 21: Deep Learning of Representations

This event is funded by DeepMind Technologies.

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