Harrah's Sand Harbor II room, Lake Tahoe, USA.
Deep Learning algorithms attempt to discover good representations, at multiple levels of abstraction. There has been rapid progress in this area in recent years, both in terms of algorithms and in terms of applications, but many challenges remain. In this workshop, we will bring together researchers interested in deep learning to review the recent technical progress, discuss the challenges, and identify promising future research directions.
The workshop invites paper submissions that will be either presented as oral or in poster format. We encourage submissions on the following (non-exhaustive) list of topics:
Through invited talks, a panel discussion and presentations by the participants, this workshop will showcase the latest advances in deep learning and address questions that are at the centre of current deep learning research (what roles do stochasticity/unsupervised learning/optimization play in deep learning, what are the desiderata for models of images/text/speech, etc.). Panel discussions will be led by the members of the organizing committee as well as by prominent representatives of the machine learning, computer vision and natural language processing communities.