The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the...

editorial board of Machine Learning resigned in order to support the Journal of Machine Learning Research (JMLR), saying that in the era of the internet, it was...

machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

conferences of high impact in machine learning and artificial intelligence research. It is supported by the International Machine Learning Society (IMLS)...

Reinforcement learning Bengio, Yoshua; Ducharme, Réjean; Vincent, Pascal (2003). "A Neural Probabilistic Language Model". Journal of Machine Learning Research. 3:...

In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...

Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. A survey from May 2020...

In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence...

Journal of Machine Learning Research. 2: 51–86. Hofmann, Thomas; Schölkopf, Bernhard; Smola, Alexander J. (2008). "Kernel methods in machine learning"...

Learning-Curve Sampling Method Applied to Model-Based Clustering". Journal of Machine Learning Research. 2 (3): 397. Archived from the original on 2013-07-15. scikit-learn...

of research areas including defence, telecommunications, the Internet of things, and pharmaceuticals. Federated learning aims at training a machine learning...

and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the...

"Exploring the limits of transfer learning with a unified text-to-text transformer". The Journal of Machine Learning Research. 21 (1): 140:5485–140:5551...

deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models...

(PDF). Journal of Machine Learning Research. 9: 937–965. Schmidhuber, Jürgen (1992). "Learning complex, extended sequences using the principle of history...

(March 2003). "A neural probabilistic language model". The Journal of Machine Learning Research. 3: 1137–1155. "Papers with Code – MLP-Mixer: An all-MLP...

Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or...

Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs...

editor-in-chief of the Journal of Machine Learning Research, a peer-reviewed open access journal on the same topics which allows researchers to publish articles...

2020). "Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey". The Journal of Machine Learning Research. 21 (1): 181:7382–181:7431...

outline is provided as an overview of, and topical guide to, machine learning: Machine learning (ML) is a subfield of artificial intelligence within computer...

linear non-Gaussian structural equation model" (PDF). The Journal of Machine Learning Research. 12: 1225–1248. arXiv:1101.2489. Archived (PDF) from the...

scientist currently serving as senior director of Artificial Intelligence and Machine Learning Research at Apple. Bengio obtained his Ph.D. in Computer...

In machine learning (ML), boosting is an ensemble metaheuristic for primarily reducing bias (as opposed to variance). It can also improve the stability...

In machine learning, feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction...

interpretable AI or explainable machine learning (XML), is a field of research that explores methods that provide humans with the ability of intellectual oversight...

(2020). "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer". Journal of Machine Learning Research. 21 (140): 1–67. arXiv:1910...

Nature Machine Intelligence is a monthly peer-reviewed scientific journal published by Nature Portfolio covering machine learning and artificial intelligence...

Quantum machine learning (QML) is the study of quantum algorithms which solve machine learning tasks. The most common use of the term refers to quantum...