Proximal algorithms are useful for obtaining solutions to difficult optimization problems, especially those involving nonsmooth or composite objective functions. A proximal algorithm is one whose ...

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world. Machine-learning algorithms are responsible for the vast majority of the artificial intelligence ...

20 Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med. 2018;178 (11):1544–7.

At the conceptual intersection of machine learning and government data collection lie Automated Suspicion Algorithms, or ASAs, which are created by applying machine learning methods to collections of ...

Machine Learning is the study of algorithms that improve automatically through experience. Topics covered typically include Bayesian Learning, Decision Trees, Genetic Algorithms, Neural Networks.

Want to understand how machine learning impacts search? Learn how Google uses machine learning models and algorithms in search.

It doesn’t take much to make machine-learning algorithms go awry The rise of large-language models could make the problem worse ...