Abstract: In recent years, support vector regression (SVR) has attracted much attention for nonlinear system identification. It can solve nonlinear problems in the form of linear expressions within ...
The goal of this code is to explore how different kernels affect the classifier’s performance. Specifically the linear and RBF (Radial Basis Function) kernels. The code involves generating data, ...
This project explores image classification using three different algorithms: Linear SVM, SVM with Radial Basis Function (RBF) Kernel, and a Multi-Layer Perceptron (MLP). The classification was ...
Transforming light: illustration of how an arbitrary linear transform can be achieved in an all-optical system using diffractive surfaces (Courtesy: Ozcan Lab/UCLA) Researchers in the US have shown ...
Abstract: 3-D controlled-source electromagnetic data are often computed directly in the domain of interest, either in the frequency domain or in the time domain. Computing it in one domain and ...
We study the profile-kernel and backfitting methods in partially linear models for clustered/longitudinal data. For independent data, despite the potential root-n inconsistency of the backfitting ...
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