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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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Problems Classification Generative modeling Regression Clustering Dimensionality reduction Density estimation Anomaly detection Data cleaning AutoML Association rules Semantic analysis Structured prediction Feature engineering Feature learning Learning to rank Grammar induction Ontology learning Multimodal learning
Supervised learning (classification • regression) Apprenticeship learning Decision trees Ensembles Bagging Boosting Random forest k-NN Linear regression Naive Bayes Artificial neural networks Logistic regression Perceptron Relevance vector machine (RVM) Support vector machine (SVM)
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
Structured prediction Graphical models Bayes net Conditional random field Hidden Markov
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
v t e

TheInternational Conference onLearning 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 highest impact and reputation 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]). It was founded by LeCun andYoshua Bengio in 2012.^[3]

Editions

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Year	Location	Country	No. of Participants^[4]	...from No. of Countries	No. of paper submissions^[5]	...thereof accepted	Acceptance rate
2026	Rio de Janeiro^[6]	Brazil	?		18,949	5,339	28.18%
2025	Singapore	Singapore	?		11,672	3,704	31.73%
2024	Vienna	Austria	6,533	79	7,304	2,260	30.94%
2023	Kigali	Rwanda	3,758	73	4,955	1,575	31.79%
2022		(virtual conference)	5,200	81	3,422	1,095	32.00%
2021	Vienna^[7]	Austria (virtual conference)	6,300	64	3,014	860	28.53%
2020	Addis Ababa^[8]^[9]	Ethiopia (virtual conference)	5,600	76	2,594	687	26.48%
2019	New Orleans,Louisiana^[10]	United States	2,600	50	1,579	502	31.79%
2018	Vancouver	Canada	1,950	38	1,013	337	33.27%
2017	Toulon	France	?		490	198	40.41%
2016	San Juan,Puerto Rico	United States	?		?
2015	San Diego,California	United States	?		?
2014	Banff National Park	Canada	?		69	69	100.00%
2013	Scottsdale,Arizona	United States	?		67	23	34.33%

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.
^Lipton, Zachary Chase."The ICLR Experiment: Deep Learning Pioneers Take on Scientific Publishing".KDnuggets. Retrieved2025-09-13.
^"13th Annual International Conference on Learning Representations (ICLR). 2025 Fact Sheet"(PDF).ICLR. 2025. Retrieved2026-01-31.
^"ICLR Statistics - Paper Copilot". 2023-01-17. Retrieved2026-01-31.
^"Future Meetings".iclr.cc. Retrieved2025-07-29.
^"ICLR 2021 Conference".openreview.net.
^"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.
^"ICLR 2019 Conference".openreview.net.

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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