Conference Information
ICLR 2022: International Conference on Learning Representations
https://iclr.cc/Conferences/2022Submission Date: |
2021-09-29 |
Notification Date: |
2022-01-24 |
Conference Date: |
2022-04-25 |
Location: |
Online |
Years: |
10 |
Viewed: 62986 Tracked: 245 Attend: 16
Call For Papers
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, robotics, health care, sustainability, music, games, 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 optimal transport 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, and interpretability
Last updated by Dou Sun in 2021-10-01
Best Papers
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Full Name | Impact Factor | Publisher |
---|---|---|
International Journal of Mobile Learning and Organisation | Inderscience | |
Engineering Computations | 1.246 | Emerald |
Journal of Machine Learning Research | Microtome Publishing | |
International Journal of Swarm Intelligence Research | IGI Global Publishing | |
Security Informatics | Springer | |
Engineering Optimization | 1.809 | Taylor & Francis |
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International Journal of E-Planning Research | IGI Global Publishing | |
Pattern Recognition | 7.740 | Elsevier |
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