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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

Learning with Kernels

Support Vector Machines, Regularization, Optimization, and Beyond

The MIT Press (2001)
CA$105.73

A comprehensive introduction to Support Vector Machines and related kernel methods.

Machine Learning for Data Streams: with Practical Examples in MOA

Machine Learning for Data Streams

with Practical Examples in MOA

Albert Bifet, Ricard Gavaldà and 2 more...
The MIT Press (2018)
CA$72.68

A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with...

Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation
The MIT Press (2012)
CA$72.68

Theory, algorithms, and applications of machine learning techniques to overcome “covariate shift”...

Learning Kernel Classifiers: Theory and Algorithms
The MIT Press (2001)
CA$66.07

An overview of the theory and application of kernel classification methods.

The Minimum Description Length Principle
The MIT Press (2007)
CA$79.29

A comprehensive introduction and reference guide to the minimum description length (MDL) Principle...

Gaussian Processes for Machine Learning
The MIT Press (2005)
CA$66.07

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled,...

Semi-Supervised Learning
The MIT Press (2010)
CA$59.47

A comprehensive review of an area of machine learning that deals with the use of unlabeled data in...

Introduction to Statistical Relational Learning
The MIT Press (2007)
CA$72.68

Advanced statistical modeling and knowledge representation techniques for a newly emerging area of...

Graphical Models for Machine Learning and Digital Communication
The MIT Press (1998)
CA$52.86

A variety of problems in machine learning and digital communication deal with complex but structured...