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math.OC2023★ 1 cited
Global relaxation-based LP-Newton method for multiple hyperparameter selection in support vector classification with feature selection
Yaru Qian, Qingna Li, Alain Zemkoho
Support vector classification (SVC) is an effective tool for classification tasks in machine learning. Its performance relies on the selection of appropriate hyperparameters. This…
math.OC2023
A Fast Smoothing Newton Method for Bilevel Hyperparameter Optimization for SVC with Logistic Loss
Yixin Wang, Qingna Li
Support vector classification (SVC) with logistic loss has excellent theoretical properties in classification problems where the label values are not continuous. In this paper, we…
math.OC2023
An Efficient Algorithm for Computational Protein Design Problem
Yukai Zheng, Weikun Chen, Qingna Li
In this paper, we consider the computational protein design (CPD) problem, which is usually modeled as a 0/1 programming and is extremely challenging due to its combinatorial prope…