Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized tw
Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimizati...
ABSTRACT This paper aims to identify the current state of the art of the latest research related to...
Support Vector Machines are a modern method assigned to the field of artificial intelligence. This m...
In this chapter we introduce basic concepts and ideas of the Support Vector Machines (SVM). In the f...
Abstract. Support vector machines (SVMs) appeared in the early nineties as optimal margin classifier...
From the beginning, machine learning methodology, which is the origin of artificial intelligence, ha...
Introduction to machine learning and support vector machines (SVM) SVM and optimization theory SVM a...
In this thesis, support vector machines (SVMs) are studied from a mathematical optimization viewpoin...
This thesis combines support vector machines with statistical models for analyzing data generated by...
Support vector machines (SVMs) are a family of machine learning methods, originally introduced for t...
We study the relation between support vector machines (SVMs) for regression (SVMR) and SVM for class...
In recent years, an enormous amount of research has been carried out on support vector machines (SVM...
In this report we show some consequences of the work done by Pontil et al. in [1]. In particular we ...
The foundations of Support Vector Machines (SVM) have been developed by Vapnik and are gaining popul...
Support Vector Machines (SVM) were developed by Vapnik [1] to solve the classification prob-lem, but...
Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimizati...
ABSTRACT This paper aims to identify the current state of the art of the latest research related to...
Support Vector Machines are a modern method assigned to the field of artificial intelligence. This m...
In this chapter we introduce basic concepts and ideas of the Support Vector Machines (SVM). In the f...
Abstract. Support vector machines (SVMs) appeared in the early nineties as optimal margin classifier...
From the beginning, machine learning methodology, which is the origin of artificial intelligence, ha...
Introduction to machine learning and support vector machines (SVM) SVM and optimization theory SVM a...
In this thesis, support vector machines (SVMs) are studied from a mathematical optimization viewpoin...
This thesis combines support vector machines with statistical models for analyzing data generated by...
Support vector machines (SVMs) are a family of machine learning methods, originally introduced for t...
We study the relation between support vector machines (SVMs) for regression (SVMR) and SVM for class...
In recent years, an enormous amount of research has been carried out on support vector machines (SVM...
In this report we show some consequences of the work done by Pontil et al. in [1]. In particular we ...
The foundations of Support Vector Machines (SVM) have been developed by Vapnik and are gaining popul...
Support Vector Machines (SVM) were developed by Vapnik [1] to solve the classification prob-lem, but...
Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimizati...
ABSTRACT This paper aims to identify the current state of the art of the latest research related to...
Support Vector Machines are a modern method assigned to the field of artificial intelligence. This m...