Sphere support vector machines for large classification tasks
This paper introduces Sphere Support Vector Machines (SVMs) as the new fast
classification algorithm based on combining a minimal enclosing ball approach, state of the …
classification algorithm based on combining a minimal enclosing ball approach, state of the …
Geometric approach to support vector machines learning for large datasets
R Strack - 2013 - scholarscompass.vcu.edu
Abstract The dissertation introduces Sphere Support Vector Machines (SphereSVM) and
Minimal Norm Support Vector Machines (MNSVM) as the new fast classification algorithms …
Minimal Norm Support Vector Machines (MNSVM) as the new fast classification algorithms …
Minimal norm support vector machines for large classification tasks
This paper introduces Minimal Norm Support Vector Machines (MNSVM) as the new fast
classification algorithm originating from minimal enclosing ball approach and based on …
classification algorithm originating from minimal enclosing ball approach and based on …
Analysis and convergence of SMO-like decomposition and geometrical algorithms for support vector machines
JL Lázaro - 2011 - dialnet.unirioja.es
Resumen Support Vector Machines (SVMs) constitute one of the most successful paradigms
in Machine Learning nowadays. Their success stems from the fact that they are relatively …
in Machine Learning nowadays. Their success stems from the fact that they are relatively …
Efficient optimization methods for regularized learning support vector machines and total-variation regularization
AB Jimenez - 2011 - dialnet.unirioja.es
In the context of machine learning methods, regularization has become an established
practice to control overfitting in the modeling process and to induce structure into the …
practice to control overfitting in the modeling process and to induce structure into the …
Cross Distance Minimization for Solving the Nearest Point Problem Based on Scaled Convex Hull
Q Leng, E Jiao, Y Liu, J Guo, Y Chen - International Conference on …, 2022 - Springer
In pattern classification, the geometric method often provides a simple and intuitive solution.
In the case of linear separability, solving the optimization hyperplane problem can be …
In the case of linear separability, solving the optimization hyperplane problem can be …
[PDF][PDF] A3: Aprendizaje Automático y Aplicaciones
JR Dorronsoro, A Suárez - ia.urjc.es
1 Project Objectives The project Aprendizaje Automático y Aplicaciones (A3, Machine
Learning and Applications) is a joint project between a research group of the Instituto de …
Learning and Applications) is a joint project between a research group of the Instituto de …