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Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.
Tibshirani was made the 2012 Statistical Society of Canada's Gold Medalist at their yearly meeting in Guelph, Ontario for "exceptional contributions to methodology and theory for the analysis of complex data sets, smoothing and regression methodology, statistical learning, and classification, and application areas that include public health ...
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (pdf). Graduate Texts in Statistics (2nd ed.). New York: Springer-Verlag. ISBN 978-0-387-84857-0. OCLC 405547558. Archived from the original on 20 November 2020
Hastie is known for his contributions to applied statistics, especially in the field of machine learning, data mining, and bioinformatics. He has authored several popular books in statistical learning, including The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
In "Introduction to Statistical Relational Learning". Edited by Lise Getoor and Ben Taskar. MIT Press. (2006) Online PDF; Klinger, R., Tomanek, K.: Classical Probabilistic Models and Conditional Random Fields. Algorithm Engineering Report TR07-2-013, Department of Computer Science, Dortmund University of Technology, December 2007. ISSN 1864 ...
Overview of the Probably Approximately Correct (PAC) Learning Framework. An introduction to the topic. L. Valiant. Probably Approximately Correct. Basic Books, 2013. In which Valiant argues that PAC learning describes how organisms evolve and learn. Littlestone, N.; Warmuth, M. K. (June 10, 1986). "Relating Data Compression and Learnability" (PDF).
John Stewart Shawe-Taylor (born 1953) is Director of the Centre for Computational Statistics and Machine Learning at University College, London (UK). His main research area is statistical learning theory. He has contributed to a number of fields ranging from graph theory through cryptography to statistical learning theory and its applications.
Statistics educators have cognitive and noncognitive goals for students. For example, former American Statistical Association (ASA) President Katherine Wallman defined statistical literacy as including the cognitive abilities of understanding and critically evaluating statistical results as well as appreciating the contributions statistical thinking can make.