MIT Press Direct is a distinctive collection of influential MIT Press books curated for scholars and libraries worldwide.
MIT Press began publishing journals in 1970 with the first volumes of Linguistic Inquiry and the Journal of Interdisciplinary History. Today we publish over 30 titles in the arts and humanities, social sciences, and science and technology.
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Established in 1962, the MIT Press is one of the largest and most distinguished university presses in the world and a leading publisher of books and journals at the intersection of science, technology, art, social science, and design.
Dataset Shift in Machine Learning
Edited by Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer and Neil D. Lawrence
An Introduction to Lifted Probabilistic Inference
Edited by Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan and David Poole
Log-Linear Models, Extensions, and Applications
Edited by Aleksandr Aravkin, Anna Choromanska, Li Deng, Georg Heigold, Tony Jebara, Dimitri Kanevsky and Stephen J. Wright
Perturbations, Optimization, and Statistics
Edited by Tamir Hazan, George Papandreou and Daniel Tarlow
Predicting Structured Data
Edited by Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola, Ben Taskar and S.V.N Vishwanathan
Optimization for Machine Learning
Edited by Suvrit Sra, Sebastian Nowozin and Stephen J. Wright
Large-Scale Kernel Machines
Edited by Léon Bottou, Olivier Chapelle, Dennis DeCoste and Jason Weston
Toward Brain-Computer Interfacing
Edited by Guido Dornhege, José del R. Millán, Thilo Hinterberger, Dennis J. McFarland and Klaus-Robert Müller
Nearest-Neighbor Methods in Learning and Vision
Edited by Gregory Shakhnarovich, Trevor Darrell and Piotr Indyk
New Directions in Statistical Signal Processing
Edited by Simon Haykin, Jose C. Principe, Terrence J. Sejnowski and John McWhirter