Boosting : foundations and algorithms

Schapire, Robert E.
Cambridge, MA : MIT Press, [2012]

Causation, prediction, and search.

Spirtes, Peter.
Cambridge, Mass. : MIT Press, [2000]
2nd ed. / Peter Spirtes, Clark Glymour, and Richard Scheines ; with additional material by David Heckerman [and others].

Gaussian processes for machine learning

Rasmussen, Carl Edward.
Cambridge, Mass. : MIT Press, [2006]

Gaussian processes for machine learning

Rasmussen, Carl Edward.
Cambridge, Mass. : MIT Press, [2006]

Graphical models for machine learning and digital communication

Frey, Brendan J.
Cambridge, Mass : MIT Press, [1998]

Introduction to statistical relational learning

Cambridge, Mass. : MIT Press, [2007]

Learning kernel classifiers : theory and algorithms

Herbrich, Ralf.
Cambridge, Mass. : MIT Press, [2002]

Learning with kernels : support vector machines, regularization, optimization, and beyond

Schölkopf, Bernhard.
Cambridge, Mass. : MIT Press, [2002]

Machine learning for data streams : with practical examples in MOA

Bifet, Albert, author.
[Piscataqay, New Jersey] : IEEE Xplore, [2018]

Machine learning in non-stationary environments : introduction to covariate shift adaptation

Sugiyama, Masashi, 1974-
Cambridge, Mass. : MIT Press, [2012]

The minimum description length principle

Grünwald, Peter D.
Cambridge, Mass. : MIT Press, [2007]

Principles of data mining

Hand, D. J. (David J.), 1950-
Cambridge, Mass. : MIT Press, 2001.

Semi-supervised learning

Cambridge, Mass. : MIT Press, [2006]