Search Results for author: Suresh Chandra

Found 6 papers, 1 papers with code

Improvement over Pinball Loss Support Vector Machine

1 code implementation2 Jun 2021 Pritam Anand, Reshma Rastogi, Suresh Chandra

The existing Pin-SVM model requires to solve the same optimization problem for all values of $\tau$ in $[ -1, 1]$.

A $ν$- support vector quantile regression model with automatic accuracy control

no code implementations21 Oct 2019 Pritam Anand, Reshma Rastogi, Suresh Chandra

The proposed $\nu$-SVQR model uses the $\nu$ fraction of training data points for the estimation of the quantiles.

A new asymmetric $ε$-insensitive pinball loss function based support vector quantile regression model

no code implementations19 Aug 2019 Pritam Anand, Reshma Rastogi, Suresh Chandra

In this paper, we propose a novel asymmetric $\epsilon$-insensitive pinball loss function for quantile estimation.

Support Vector Regression via a Combined Reward Cum Penalty Loss Function

no code implementations28 Apr 2019 Pritam Anand, Reshma Rastogi, Suresh Chandra

In this paper, we introduce a novel combined reward cum penalty loss function to handle the regression problem.

Learning a hyperplane regressor by minimizing an exact bound on the VC dimension

no code implementations16 Oct 2014 Jayadeva, Suresh Chandra, Siddarth Sabharwal, Sanjit S. Batra

The capacity of a learning machine is measured by its Vapnik-Chervonenkis dimension, and learning machines with a low VC dimension generalize better.

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