ICLR @ Addis Ababa ·The Eighth International Conference on Learning Representations
Sun Apr 26th through Thu the 30th

Affinity Group Activities

Please visit the Diversity & Inclusion page for scheduled program and activities.

Registration 

Register 01/21 » 

Registration Cancellation Policy »

Calls

 

General Chair

  • Alexander Rush, Cornell Tech

Senior Program Chair

  • Shakir Mohamed, Google DeepMind

Program Chairs

  • Dawn Song, UC Berkeley 
  • Kyunghyun Cho, NYU 
  • Martha White, University of Alberta

Workshop Chairs

  • Gabriel Synnaeve, Facebook AI Research
  • Asja Fischer, Ruhr University Bochum

Diversity+Inclusion Chairs

  • Animashree Anandkumar - Cal Tech / NVidia
  • Kevin Swersky - Google AI

Contact

The organizers can be contacted here.

Sponsors

The ICLR 2020 Sponsor Portal will open in the last quarter of 2019.  New sponsors to ICLR, please email us at 2020 ICLR Sponsor Prospectus Request, provide your contact information and you will receive the ICLR 2020 Sponsor Prospectus when it becomes available.  If you were a sponsor at ICLR 2019 then you will receive the ICLR 2020 Sponsor Prospectus via email when it becomes available as well. 
 
 

Important Dates

Workshops Sun Apr 26th
Conference Sessions Sun Apr 26th through Thu the 30th
Workshop Application Open Sept. 4, 2019, noon *
Paper Submission deadline Sept. 25, 2019, 8 a.m. *
Workshop Application Close Oct. 25, 2019, 11 p.m. *
Paper Rebuttal/discussion ends Nov. 15, 2019, 2 p.m. *
Workshop Proposal Notifications Nov. 27, 2019, 2 p.m. *
Sponsor Portal Open Dec. 17, 2019, 8 a.m. *
Paper Decision Notification Dec. 19, 2019, 2 p.m. *
Registration Opens Jan. 21, 2020, 8 a.m. *
Workshop Organizers Announce Decisions Feb. 25, 2020, 6 p.m. *
All dates » * Dates above are in pacific time

About Us

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