The phrase "computational learning" is correct and commonly used in written English.
It refers to the study and application of algorithms and computer programs to facilitate learning and problem-solving. Example: "The field of artificial intelligence relies heavily on computational learning to improve and develop advanced technologies."
In such cases, many issues can be addressed by means of machine learning algorithms, resulting from the theories on pattern recognition and computational learning.
Computational learning theory provides distribution-free bounds on generalisation accuracy in terms of a classifier's capacity, related to model complexity (Vapnik, 1998).
His research focuses on algorithms for massive data sets, verifiable computation and computational learning theory.
Because many developments in, and applications of, formal learning theory come from computer science, the term "computational learning theory" is also common.
This relates to computational learning theory, a branch of theoretical computer science that is concerned with the computational analysis of machine learning algorithms and their performance in relation to different application domains' ([19], p. 172).
Leslie G. Valiant has been named the winner of the 2010 ACM A.M. Turing Award for his fundamental contributions to the development of computational learning theory and to the broader theory of computer science.
The sequential decision-making task provides an ecologically valid framework for investigating computational-learning signals used in reward harvesting.
In two complementary experiments with independent samples, participants completed a sequential decision task that dissociated two computational-learning mechanisms, model-based and model-free.
Rebecca Passonneau is the Director of Columbia University's Center for Computational Learning Systems (CCLS), where she is also a Senior Research Scientist in computational linguistics.
He left to help create the Center for Computational Learning Systems at Columbia, where he was director.
Smaranda Muresan is a Research Scientist at the Center for Computational Learning Systems at Columbia University.
