ICLR 2019

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ICLR 2019
Seventh International Conference on Learning Representations
Event in series ICLR
Dates 2019/05/06 (iCal) - 2019/05/09
Homepage: https://iclr.cc/Conferences/2019
Submitting link: https://openreview.net/group?id=ICLR.cc/2019/Conference
Location: New Orleans, Louisiana, USA
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Important dates
Submissions: 2018/09/27
Notification: 2018/12/22
Papers: Submitted 1591 / Accepted 500 (31.4 %)
General chairs: Tara Sainath, Alexander Rush
PC chairs: Sergey Levine, Karen Livescu, Shakir Mohamed
Workshop chairs: Been Kim, Graham Taylor
Table of Contents


The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics. Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.


A non-exhaustive list of relevant topics explored at the conference include:

  • unsupervised, semi-supervised, and supervised representation learning
  • representation learning for planning and reinforcement learning
  • metric learning and kernel learning
  • sparse coding and dimensionality expansion
  • hierarchical models
  • optimization for representation learning
  • learning representations of outputs or states
  • implementation issues, parallelization, software platforms, hardware
  • applications in vision, audio, speech, natural language processing, robotics, neuroscience, or any other field