Machine Learning (ML)

Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.
相关学科: SVMTime SeriesAIConvolutionNeural and Evolutionary ComputingCVLSTMLogistic RegressionEEGLinear Regression









Eric S. Lander

624670 被引用,865 篇论文

Douglas G. Altman

596830 被引用,1073 篇论文

Yoshua Bengio

429868 被引用,1063 篇论文

Geoffrey E. Hinton

345738 被引用,408 篇论文

Steven L. Salzberg

281631 被引用,443 篇论文

Robert Tibshirani

278725 被引用,644 篇论文

Todd R. Golub

272660 被引用,495 篇论文

Ralph B. D'Agostino

225766 被引用,1426 篇论文

David Haussler

210533 被引用,548 篇论文

Donald B. Rubin

207461 被引用,567 篇论文