Search Results for author:
Found 6 papers, 1 papers with code
Learning a hyperplane regressor by minimizing an exact bound on the VC dimension
The capacity of a learning machine is measured by its Vapnik-Chervonenkis dimension, and learning machines with a low VC dimension generalize better.
Support Vector Regression via a Combined Reward Cum Penalty Loss Function
In this paper, we introduce a novel combined reward cum penalty loss function to handle the regression problem.
A new asymmetric $ε$-insensitive pinball loss function based support vector quantile regression model
In this paper, we propose a novel asymmetric $\epsilon$-insensitive pinball loss function for quantile estimation.
A $ν$- support vector quantile regression model with automatic accuracy control
The proposed $\nu$-SVQR model uses the $\nu$ fraction of training data points for the estimation of the quantiles.
Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images
We show that popular choices of dataset selection suffer from data homogeneity, leading to misleading results.
Improvement over Pinball Loss Support Vector Machine
The existing Pin-SVM model requires to solve the same optimization problem for all values of $\tau$ in $[ -1, 1]$.
