ESI17
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Systematic approaches to deep learning methods for audio
11.-15. September 2017 Erwin Schroedinger Institute (Univ. Vienna)
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PROGRAM
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so see the actual program!
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so see the abstracts of talks/posters!
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Plenary/Public Talks:
There will be two or three extended lectures introducing central concepts of deep learning from a mathematical and machine learning perspective, respectively. The following colleagues have already confirmed their talks:
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Philipp Grohs, NuHAG, University of Vienna:
Deep learning as a mathematician: Conjectures, proofs and open questions
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Jan Schlueter, Austrian Research Institute for Artificial Intelligence
Deep learning as an engineer: The nuts and bolts and dirty tricks
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designed by -hSc-
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