A Safe Screening Rule with Bi-level Optimization of $\nu$ Support Vector Machine

arXiv:2403.01769v1 Announce Type: new
Abstract: Support vector machine (SVM) has achieved many successes in machine learning, especially for a small sample problem. As a famous extension of the traditional SVM, the $\nu$ support vector machine ($\nu$-SVM) has shown outstanding performance due to its great model interpretability. However, it still faces challenges in training overhead for large-scale problems. To address this issue, we propose a safe screening rule with bi-level optimization for $\nu$-SVM (SRBO-$\nu$-SVM) which can screen out inactive samples before …

abstract arxiv cs.ai cs.lg extension interpretability machine machine learning math.oc model interpretability optimization performance sample screening small support svm type vector