Learning with Smooth Hinge Losses
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.08.060
Abstract: Due to the non-smoothness of the Hinge loss in SVM, it is difficult to obtain a faster convergence rate with modern optimization algorithms. In this paper, we introduce two smooth Hinge losses $\psi_G(\alpha;\sigma)$ and $\psi_M(\alpha;\sigma)$… read more here.
Keywords: hinge loss; smooth hinge; loss; hinge ... See more keywords
An analytic theory of shallow networks dynamics for hinge loss classification
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Statistical Mechanics: Theory and Experiment"
DOI: 10.1088/1742-5468/ac3a76
Abstract: Neural networks have been shown to perform incredibly well in classification tasks over structured high-dimensional datasets. However, the learning dynamics of such networks is still poorly understood. In this paper we study in detail the… read more here.
Keywords: classification; hinge loss; theory shallow; analytic theory ... See more keywords
Robust Rescaled Hinge Loss Twin Support Vector Machine for Imbalanced Noisy Classification
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2914465
Abstract: Support vector machine (SVM) and twin SVM (TWSVM) are sensitive to the noisy classification, due to the unlimited measures in their losses, especially for imbalanced classification problem. In this paper, by combining the advantages of… read more here.
Keywords: hinge loss; noisy classification; loss; support vector ... See more keywords