[robotics-worldwide] [news] New Frontiers for Deep Learning in Robotics Workshop at RSS 2017: First Call for Submissions
In this workshop renowned experts will discuss deep learning techniques at the frontiers of research that are not yet widely adopted, discussed, or well-known in our community. The workshop is set up to target selected research topics such as Bayesian deep learning, generative models, deep reinforcement learning for planning and navigation and transdisciplinary approaches that are of high relevance with potential ground-breaking implications for robotic perception, learning, and control. The workshop will introduce these techniques to a robotics audience while also exposing participants from the machine learning community to real-world problems encountered by robotics researchers who apply deep learning in their research.
This workshop is the successor to the highly popular "Deep Learning in Robotics" workshop at last year's Robotics: Science and Systems conference. Our goal is to bring researchers from the machine learning and robotics communities together to discuss and analyse the limits and potentials of new deep learning techniques, as well as propose directions for future joint research between our communities.
More details on the workshop, speaker line up and submission details can be found here:
We look forward to seeing everyone in Boston in July!
With best regards from the organizers:
Niko Suenderhauf, Jurgen Leitner, Michael Milford and Peter Corke, Australian Centre for Robotic Vision (ACRV), Queensland University of Technology (QUT)
Pieter Abbeel, UC Berkeley
Michael Milford | Associate Professor | ARC Future Fellow | Microsoft Research Faculty Fellow | Chief Investigator, Australian Centre for Robotic Vision
Australian Centre for Robotic Vision | Electrical Engineering and Computer Science School
Science and Engineering Faculty | Queensland University of Technology
S Block, Room S1110, Gardens Point Campus
ph 3138 9969 | email [hidden email] CRICOS No 00213J
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