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International Conference on Learning Representations

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Academic conference in machine learning

International Conference on Learning Representations

Abbreviation	ICLR
Discipline	Machine learning,artificial intelligence,feature learning
Publication details
History	2013–present
Frequency	Annual
Open access	yes (on openreview.net)
Website	https://iclr.cc/

Machine learning anddata mining
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Clustering BIRCH CURE Hierarchical k-means Fuzzy Expectation–maximization (EM) DBSCAN OPTICS Mean shift
Dimensionality reduction Factor analysis CCA ICA LDA NMF PCA PGD t-SNE SDL
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Anomaly detection RANSAC k-NN Local outlier factor Isolation forest
Neural networks Autoencoder Deep learning Feedforward neural network Recurrent neural network LSTM GRU ESN reservoir computing Boltzmann machine Restricted GAN Diffusion model SOM Convolutional neural network U-Net LeNet AlexNet DeepDream Neural field Neural radiance field Physics-informed neural networks Transformer Vision Mamba Spiking neural network Memtransistor Electrochemical RAM (ECRAM)
Reinforcement learning Q-learning Policy gradient SARSA Temporal difference (TD) Multi-agent Self-play
Learning with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF
Model diagnostics Coefficient of determination Confusion matrix Learning curve ROC curve
Mathematical foundations Kernel machines Bias–variance tradeoff Computational learning theory Empirical risk minimization Occam learning PAC learning Statistical learning VC theory Topological deep learning
Journals and conferences AAAI ECML PKDD NeurIPS ICML ICLR IJCAI ML JMLR
Related articles Glossary of artificial intelligence List of datasets for machine-learning research List of datasets in computer vision and image processing Outline of machine learning
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TheInternational Conference on Learning Representations (ICLR) is amachine learning conference typically held in late April or early May each year. Along withNeurIPS andICML, it is one of the three primary conferences of high impact inmachine learning andartificial intelligence research.^[1]

Theconference includes invited talks as well as oral and poster presentations of refereed papers. Since its inception in 2013, ICLR has employed anopen peer review process to referee paper submissions (based on models proposed byYann LeCun^[2]). In 2019, there were 1591 paper submissions, of which 500 accepted with poster presentations (31%) and 24 with oral presentations (1.5%).^[3] In 2021, there were 2997 paper submissions, of which 860 were accepted (29%).^[4] It was founded by LeCun andYoshua Bengio in 2012.^[5]

Locations

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ICLR 2026,Rio de Janeiro,Brazil^[6]
ICLR 2025,Singapore
ICLR 2024,Vienna,Austria
ICLR 2023,Kigali,Rwanda
ICLR 2022 (virtual conference)
ICLR 2021,Vienna,Austria (virtual conference)
ICLR 2020,Addis Ababa,Ethiopia (virtual conference)^[7]^[8]
ICLR 2019,New Orleans,Louisiana,United States
ICLR 2018,Vancouver,Canada
ICLR 2017,Toulon,France
ICLR 2016,San Juan,Puerto Rico,United States
ICLR 2015,San Diego,California,United States
ICLR 2014,Banff National Park,Canada
ICLR 2013,Scottsdale,Arizona,United States

References

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^"Artificial Intelligence - Google Scholar Metrics".scholar.google.es. Retrieved2024-07-10.
^"Proposal for A New Publishing Model in Computer Science".yann.lecun.com.
^"ICLR 2019 Conference".openreview.net.
^"ICLR 2021 Conference".openreview.net.
^Lipton, Zachary Chase."The ICLR Experiment: Deep Learning Pioneers Take on Scientific Publishing".KDnuggets. Retrieved2025-09-13.
^"Future Meetings".iclr.cc. Retrieved2025-07-29.
^"Major AI conference is moving to Africa in 2020 due to visa issues". 19 November 2018.
^"Major AI conference is moving to Africa in 2020 due to visa issues".VentureBeat. 2018-11-19. Retrieved2020-10-07.

External links

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Official website

v t e Differentiable computing
General	Differentiable programming Information geometry Statistical manifold Automatic differentiation Neuromorphic computing Pattern recognition Ricci calculus Computational learning theory Inductive bias
Hardware	IPU TPU VPU Memristor SpiNNaker
Software libraries	TensorFlow PyTorch Keras scikit-learn Theano JAX Flux.jl MindSpore
Portals Computer programming Technology

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