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...

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...

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

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

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

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...

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

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

explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual...

Quantum machine learning is the integration of quantum algorithms within machine learning programs. The most common use of the term refers to machine learning...

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

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...

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

"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...

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

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

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

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

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

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

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...

Journal of Machine Learning Research. 15 (1): 1929–1958. Archived (PDF) from the original on 2016-01-19. Retrieved 2015-01-03. "Regularization of Neural...

relational learning (SRL) framework for modeling probabilistic and relational domains. It is applicable to a variety of machine learning problems, such...

Globerson, Amir (2007). "Euclidean Embedding of Co-occurrence Data" (PDF). Journal of Machine Learning Research. Qureshi, M. Atif; Greene, Derek (2018-06-04)...

(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...