Connectionists: 1st KDD Deep Learning Day, August 20th, London: Call for Papers

[Joan Bruna Estrach]

KDD 2018 Deep Learning Day Call for Papers

KDD 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 Information—- 

Submission Website: https://easychair.org/conferences/?conf=dlday18  <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 and a poster for presentation. At least one author of each accepted paper is required to present their work in the poster session at the workshop. 

—- Topics of Interest—- 

Topic areas for the workshop include (but are not limited to) the following: 

Unsupervised, semi-supervised, and supervised representation learning on various kinds of data (images, text, graphs, time series, etc.)
Interpretable deep learning
Hierarchical models
Reinforce learning
Optimization for deep learning
Multimodal deep learning
Theory of deep learning
Applications in vision, audio, speech, natural language processing, and human computer interaction
Applications in healthcare analytics and neuroscience
Applications in social computing, fraud detection, or any other field

—- Important Dates—- 

Workshop paper submissions: July 1st, 2018 

Paper acceptance notifications: July 15th, 2018 

Camera-ready submission: August 1st, 2018 


—- General Chairs—- 

Anima Anandkumar, Caltech/Amazon 

Jure Leskovec, Stanford/Pinterest 

Joan Bruna, NYU 


—- Program Chairs—- 

Xia “Ben” Hu, Texas A&M University 


Yuxiao Dong, Microsoft Research


More information at

http://www.kdd.org/kdd2018/calls/view/kdd-2018-deep-learning-day-call-for-papers <http://www.kdd.org/kdd2018/calls/view/kdd-2018-deep-learning-day-call-for-papers>
http://www.kdd.org/kdd2018/deep-learning-day <http://www.kdd.org/kdd2018/deep-learning-day>
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