IEEE

Adaptive Kernel Optimization for Probabilistic Learning: Integrating Support Vector Machines with Gaussian Process Frameworks

Abstract: With its robust capabilities for non-linear regression and classification, kernel-based learning has emerged as a fundamental component of state-of-the-art machine learning approaches. In ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
IEEE

Support Vector Machine Detection Strategies for Different Types of Faults

Abstract: In this study, the application of support vector machine (SVM) in modern industrial fault diagnosis is mainly analyzed. As an advanced machine learning algorithm, SVM can effectively ...