19 citations · 25 across the 5 of their papers we have counts for
3 papers · 1 filter
An Active Instance-based Machine Learning method for Stellar Population Studies
Thamar Solorio, Olac Fuentes, Roberto Terlevich +1
We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optim…
Automated Determination of Stellar Population Parameters in Galaxies Using Active Instance-based Learning
Thamar Solorio, Olac Fuentes, Roberto Terlevich +2
In this work we focus on the determination of the relative distributions of young, intermediate-age and old populations of stars in galaxies. Starting from a grid of theoretical po…
Age determination of the nuclear stellar population of Active Galactic Nuclei using Locally Weighted Regression
Trilce Estrada-Piedra, Juan Pablo Torres-Papaqui, Roberto Terlevich +2
We present a new technique to segregate old and young stellar populations in galactic spectra using machine learning methods. We used an ensemble of classifiers, each classifier in…