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This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-worl...

Materias / palabras clave: Support vector machine; Dimension (graph theory); Generalization; Structural risk minimization; Mathematical proof; Computer science; Kernel (algebra); VC dimension; Separable space; Construct (python library); Polynomia...

Materias / palabras clave: Classifier (UML); Gene; Computer science; Feature selection; Redundancy (engineering); Gene selection; Support vector machine; Computational biology; sort; Artificial intelligence; Pattern recognition (psychology); Data ...

Materias / palabras clave: Computational intelligence; Support vector machine; Least squares support vector machine; Quadratic programming; Benchmark (surveying); Set (abstract data type); Computer science; Quadratic equation; Mathematics; Artific...

"In agitated systems, the phase inversion (PI) phenomenon – the mechanism by which a dispersed phase becomes the continuous one – has been studied extensively in an empirical manner and few models have been put for...

"SAR (synthetic aperture radar) and PolSAR (polarimetric synthetic aperture radar) images fulfill a fundamental role in Earth observation, due to their advantages over optical images. However, the presence of speckle noi...

Materias / palabras clave: Feature vector; Generalization; Support vector machine; Artificial intelligence; Computer science; Relevance vector machine; Structured support vector machine; Dimension (graph theory); Benchmark (surveying); Vector spac...

Materias / palabras clave: Support vector machine; Computer science; Regularization (linguistics); Quadratic programming; Perspective (graphical); Machine learning; Relevance vector machine; Function (biology); Regular polygon; Artificial intellig...

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.

Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the dif...

LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popul...

We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object det...

Materias / palabras clave: Random forest; Mathematics; AdaBoost; Statistics; Tree (set theory); Generalization; Support vector machine; Generalization error; Measure (data warehouse); Artificial intelligence; Pattern recognition (psychology); Comp...

Covers supervised learning (prediction) to unsupervised learning. This book contains topics including neural networks, support vector machines, classification trees and boosting

"Falls pose a significant health risk to older adults, often resulting in serious injuries and reduced independence. This study explored two machine learning approaches for detecting falls using data from wearable sensor...

There s some very important meaning in the study of realtime face recognition and tracking system for the video monitoring and artifical vision. The current method is still very susceptible to the illumination condition,...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be...

A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Mach...