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.

KDD Deep Learning Day will be held on Monday, August, 20, 2018

—- Submission Information—-

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, student authors can register for KDD 2018 early-bird registration rates.

—- 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 1, 2018

Paper acceptance notifications: July 15, 2018

Camera-ready submission: August 1, 2018

—- General Chairs—-

Anima Anandkumar, Caltech/Amazon

Jure Leskovec, Stanford/Pinterest

Joan Bruna, NYU

—- Organizing Committee—-

Yuxiao Dong, Microsoft Research

Pierre Richemond, Imperial College London

Douglas Mcilwraith, Imperial College London

Kevin Webster, Imperial College London

Xia “Ben” Hu, Texas A&M University