DLDay'18: The ACM KDD 2018 Deep Learning Day London, UK, August 20, 2018 |
Conference website | http://www.kdd.org/kdd2018/deep-learning-day |
Submission link | https://easychair.org/conferences/?conf=dlday18 |
Submission deadline | July 1, 2018 |
The ACM KDD 2018 Deep Learning Day aims to provide an opportunity for participants from academia, industry, government and other related parties to present and discuss novel ideas on current and emerging topics relevant to deep learning.
The KDD Deep Learning Day provides a single big plenary schedule with exciting invited speakers and leaders from both academia and industry, paper spotlight presentations, and a poster session.
We wish to exchange ideas on recent approaches to the challenges related to deep structures, identify emerging fields of applications for such techniques, and provide opportunities for relevant interdisciplinary research or projects.
Submission Guidelines
Submission Website: https://easychair.org/conferences/?conf=dlday18
The submitted manuscripts must be formatted according to the Standard ACM Conference Proceedings Template. The maximum length of papers is 10 pages in this format -- shorter papers are also welcome. The paper submission should be in PDF. The accepted papers will be published on the workshop's website, and will not be considered archival. This is intended to help preserve the authors’ ability to submit a revised version of their paper to a conference or journal. All submissions should clearly present the author information including the names of the authors, the affiliations and the emails.
Authors of all accepted papers must prepare a final version for publication. At least one author of each accepted paper is required to present their work in the oral spotlight and the poster session at the KDD 2018 Deep Learning Day. For accepted DL Day papers, authors can register for KDD 2018 early-bird registration rates.
List of Topics
Topic areas for the workshop include (but are not limited to) the following:
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Unsupervised, semi-supervised, and supervised representation learning on various kinds of data (images, text, graphs, time series, etc.)
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Interpretable deep learning
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Hierarchical models
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Reinforce learning
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Optimization for deep learning
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Multimodal deep learning
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Theory of deep learning
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Applications in vision, audio, speech, natural language processing, and human computer interaction
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Applications in healthcare analytics and neuroscience
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Applications in social computing, fraud detection, or any other field
Committees
General Chairs
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Anima Anandkumar, Caltech/Amazon
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Jure Leskovec, Stanford/Pinterest
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Joan Bruna, NYU
Organizing Committee
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Pierre Richemond, Imperial College London
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Douglas Mcilwraith, Imperial College London
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Kevein Webster, Imperial College London
Program Chairs
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Xia “Ben” Hu, Texas A&M University
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Yuxiao Dong, Microsoft Research
Venue
The Deep Learning Day is a plentary full day event in KDD 2018, which will be held at ExCeL, the international exhibition and conference centre located in East London. Detailed information can be found at http://www.kdd.org/kdd2018/venue.
Contact
All questions about submissions should be emailed to dlday18 [at] easychair.org.