WebIn this paper, we propose a novel classifier termed as twin-parametric margin support vector machine with truncated pinball loss (TPin-TSVM), which is motivated by the twin-parametric margin support vector machine (TPMSVM). The proposed TPin-TSVM has the following characteristics. Firstly, it can preserve both sparsity and feature noise ... Web1. jún 2024 · A novel sparse pin-ENR with the elastic net regularization and pinball loss is first proposed for MLC to improve the interpretability and robustness in this paper. It is …
Convex-constrained Sparse Additive Modeling and Its Extensions
Web1. máj 2024 · Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. In this work we show how shape constraints such as convexity/concavity and their extensions, can be integrated into additive models. The proposed sparse difference of convex additive models (SDCAM) can estimate most … WebExtensive research on pinball loss has been conducted, leading to the development and application of the sparse ε-insensitive pinball loss and the twin pinball SVR . Several studies have been conducted to address the outlier problem, with a focus on developing a non-convex loss function. ... Yang, L.; Dong, H. Support vector machine with ... garfield western apply for grant
dblp: Hong Chen 0004
WebSAM is short for sparse additive modeling, and adopts the computationally efficient basis spline technique. We solve the optimization problems by various computational algorithms including the block coordinate descent algorithm, fast iterative soft-thresholding algorithm, and newton method. WebSparse additive machine with pinball loss Author links open overlay panel Yingjie Wang a 1 , Xin Tang b 1 , Hong Chen c , Tianjiao Yuan d , Yanhong Chen d , Han Li a Show more Web12. jan 2024 · This paper proposes a SVM classifier with the pinball loss, called pin-SVM, and investigates its properties, including noise insensitivity, robustness, and … black pepper spam discontinued