Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Vila, Àlex"'
The introduction of machine learning (ML) techniques to the field of survival analysis has increased the flexibility of modeling approaches, and ML based models have become state-of-the-art. These models optimize their own cost functions, and their p
Externí odkaz:
http://arxiv.org/abs/2302.12059
Autor:
Marco-Benedí, Victoria ⁎, Cenarro, Ana, Laclaustra, Martín, Calmarza, Pilar, Bea, Ana M., Vila, Àlex, Morillas-Ariño, Carlos, Puzo, José, Mediavilla Garcia, Juan Diego, Fernández Alamán, Amalia Inmaculada, Suárez Tembra, Manuel, Civeira, Fernando
Publikováno v:
In Clínica e Investigación en arteriosclerosis (English edition) March-April 2024 36(2):71-77
Autor:
Marco-Benedí, Victoria, Cenarro, Ana, Laclaustra, Martín, Calmarza, Pilar, Bea, Ana M., Vila, Àlex, Morillas-Ariño, Carlos, Puzo, José, Mediavilla Garcia, Juan Diego, Fernández Alamán, Amalia Inmaculada, Suárez Tembra, Manuel, Civeira, Fernando
Publikováno v:
In Clinica e Investigacion en Arteriosclerosis March-April 2024 36(2):71-77
The foundational concept of Max-Margin in machine learning is ill-posed for output spaces with more than two labels such as in structured prediction. In this paper, we show that the Max-Margin loss can only be consistent to the classification task un
Externí odkaz:
http://arxiv.org/abs/2105.15069
Max-margin methods for binary classification such as the support vector machine (SVM) have been extended to the structured prediction setting under the name of max-margin Markov networks ($M^3N$), or more generally structural SVMs. Unfortunately, the
Externí odkaz:
http://arxiv.org/abs/2007.01012
We present a novel approach to image restoration that leverages ideas from localized structured prediction and non-linear multi-task learning. We optimize a penalized energy function regularized by a sum of terms measuring the distance between patche
Externí odkaz:
http://arxiv.org/abs/2006.09261
Publikováno v:
In Clínica e Investigación en arteriosclerosis (English edition) November-December 2023 35(6):272-279
Autor:
Marco-Benedí, Victoria, Cenarro, Ana, Vila, Àlex, Real, José T., Tamarit, Juan J., Walther, Luis A. Alvarez-Sala, Diaz-Diaz, José Luis, Perea, Verónica, Civeira, Fernando, Vaz, Antonio J. Vallejo
Publikováno v:
In Journal of Clinical Lipidology November-December 2023 17(6):717-731
Publikováno v:
In Clinica e Investigacion en Arteriosclerosis November-December 2023 35(6):272-279
In this work we provide a theoretical framework for structured prediction that generalizes the existing theory of surrogate methods for binary and multiclass classification based on estimating conditional probabilities with smooth convex surrogates (
Externí odkaz:
http://arxiv.org/abs/1902.01958