Deep Learning Day

The impact of deep learning in data science has of course been nothing less than transformative. Powered by the surge in modern compute capacities, widespread data availability, and advances in coding frameworks, deep neural networks are now ubiquitous. Deep methods yield state-of-the-art performance on many domains (computer vision, speech recognition and generation, natural language processing), and are still widening their lead as more research appears daily. But the last couple years, the field has matured, just as it was expanding rapidly. A debate is now happening between practitioners and theorists. Methods have clearly gotten more abstract, and the focus is shifting towards more rigorous and robust experiments, and more interpretative theory in order to further develop the great empirical successes that we see.

For the first time at KDD, we are organizing a full Deep Learning Day as a key event, specifically dedicated to the field. The goal will be to provide a clear, wide overview of recent developments in deep learning, including emerging topics deserving of more attention, such as graph convolutional neural networks or computational optimal transport. During the day, we will welcome many diverse and exciting invited speakers from world class research institutions. Tutorials will be organized, and a panel debate will conclude the day. Stay tuned for upcoming program announcements, and don't miss it!

Chairs

Anima Anandkumar
Anima Anandkumar
CALTECH/Amazon
Jure Leskovec
Jure Leskovec
Stanford/Pinterest

Organizing Committee

Joan Bruna
Joan Bruna
NYU
Pierre Richemond
Pierre Richemond
IMPERIAL COLLEGE LONDON
Douglas Mcilwraith
Douglas Mcilwraith
IMPERIAL COLLEGE LONDON
Kevin Webster
Kevin Webster
IMPERIAL COLLEGE LONDON

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KDD 2018 - London, United Kingdom. 19 - 23 August 2018

The annual KDD conference is the premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.

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