Data Mining techniques often ask for the resolution of optimization problems. Supervised Classification, and, in particular, Support Vector Machines, can be seen as a paradigmatic instance. In this paper, some links between Mathematical Optimization methods and Supervised Classification are emphasized. It is shown that many different areas of Mathematical Optimization play a central role in off-the-shelf Supervised Classification methods. Moreover, Mathematical Optimization turns out to be extremely useful to address important issues in Classification, such as identifying relevant variables, improving the interpretability of classifiers or dealing with vagueness/noise in the data.Ministerio de Ciencia e InnovaciónJunta de Andalucí
In this thesis, support vector machines (SVMs) are studied from a mathematical optimization viewpoin...
In this thesis we explore different mathematical techniques for extracting information from data. In...
My dissertation deals with the research areas optimization and machine learning. However, both of th...
The Supervised Classification problem, one of the oldest and most recurrent problems in applied data...
Classical optimization techniques have found widespread use in machine learning. Convex optimization...
Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessibl...
Support Vector Machine (SVM) is one of the most important class of machine learning models and algor...
Optimization and machine learning are both extremely active research topics. In this thesis, we expl...
Introduction to machine learning and support vector machines (SVM) SVM and optimization theory SVM a...
Thesis: Ph. D. in Mathematics and Operations Research, Massachusetts Institute of Technology, Depart...
Machine learning problems of supervised classification, unsupervised clustering and parsimonious app...
Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimizati...
© Published under licence by IOP Publishing Ltd. In the article several optimization models are cons...
Abstract—Optimization is considered to be one of the pillars of statistical learning and also plays ...
The present book contains the 10 articles finally accepted for publication in the Special Issue “Com...
In this thesis, support vector machines (SVMs) are studied from a mathematical optimization viewpoin...
In this thesis we explore different mathematical techniques for extracting information from data. In...
My dissertation deals with the research areas optimization and machine learning. However, both of th...
The Supervised Classification problem, one of the oldest and most recurrent problems in applied data...
Classical optimization techniques have found widespread use in machine learning. Convex optimization...
Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessibl...
Support Vector Machine (SVM) is one of the most important class of machine learning models and algor...
Optimization and machine learning are both extremely active research topics. In this thesis, we expl...
Introduction to machine learning and support vector machines (SVM) SVM and optimization theory SVM a...
Thesis: Ph. D. in Mathematics and Operations Research, Massachusetts Institute of Technology, Depart...
Machine learning problems of supervised classification, unsupervised clustering and parsimonious app...
Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimizati...
© Published under licence by IOP Publishing Ltd. In the article several optimization models are cons...
Abstract—Optimization is considered to be one of the pillars of statistical learning and also plays ...
The present book contains the 10 articles finally accepted for publication in the Special Issue “Com...
In this thesis, support vector machines (SVMs) are studied from a mathematical optimization viewpoin...
In this thesis we explore different mathematical techniques for extracting information from data. In...
My dissertation deals with the research areas optimization and machine learning. However, both of th...