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2016 IEEE Pacific Visualization Symposium (PacificVis) (2016)
Taipei, Taiwan
April 19, 2016 to April 22, 2016
ISSN: 2165-8773
ISBN: 978-1-5090-1451-4
pp: xiv
Tzi-Cker Chiueh , Information And Communication Labs, Industrial Technology Research Institute, Taiwan
ABSTRACT
The enormous successes of deep learning in many domains such as video, audio, speech, text, sequence, etc. has swept the aca-demia and industry alike, to the extent that many are touting deep learning training as an alternative form of programming future applications. Amid this excitement lies a more sombre question: if training for deep learning models is compared to software coding, what is the integrated development environment (IDE) for deep learning training? Specifically, what are the debugging and analysis tools required for manually refining and evolving a deep learning model towards its final form? In this presentation, I will survey related work in this area and outline the visualization requirements of a deep learning IDE that we are currently working on.
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CITATION
Tzi-Cker Chiueh, "Keynote speaker: Visualization for deep learning training", 2016 IEEE Pacific Visualization Symposium (PacificVis), vol. 00, no. , pp. xiv, 2016, doi:10.1109/PACIFICVIS.2016.7465243
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