ICLR 2021 - Ninth International Conference on Learning Representations

We invite submissions to the 2021 International Conference on Learning Representations, and welcome paper submissions from all areas of machine learning and deep learning.
Key dates
The planned dates are as follow:
Abstract submission: 28 September 2020, 08:00 AM PDT
Submission date: 2 October 2020, 08:00 AM PDT
Reviews released: 10 November 2020
Author discussion period ends: 24 November 2020
Final decisions: 12 January 2021
Subject Areas
We consider a broad range of subject areas including feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization, as well as applications in vision, speech recognition, text understanding, games, music, computational biology, and others.
A non-exhaustive list of relevant topics:
unsupervised, semi-supervised, and supervised representation learning
representation learning for planning and reinforcement learning
representation learning for computer vision and natural language processing
metric learning and kernel learning
sparse coding and dimensionality expansion
hierarchical models
optimization for representation learning
learning representations of outputs or states
theoretical issues in deep learning
visualization or interpretation of learned representations
implementation issues, parallelization, software platforms, hardware
applications in audio, speech, robotics, neuroscience, computational biology, or any other field
societal considerations of representation learning including fairness, safety, privacy