ICML 2017, Sydney, Australia August 10, 2017
All talks at the workshop were video recorded and the videos will be available soon!
The recent advancements in deep learning have revolutionized the field of machine learning, enabling unparalleled performance and many new real-world applications. Yet, the developments that led to this success have often been driven by empirical studies, and little is known about the theory behind some of the most successful approaches. While theoretically well-founded deep learning architectures had been proposed in the past, they came at a price of increased complexity and reduced tractability. Recently,
Gauthier Gidel
Andrzej Pronobis
Tegan Maharaj
CHU WEI's HOMEPAGE
dimitri-mar.github.io
CHU WEI's HOMEPAGE
Jörn-Henrik Jacobsen
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