• Neural networks as an optimization tool for regression 

      Coscrato, Victor Azevedo (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 02/09/2019)
      Neural networks are a tool to solve prediction problems that have gained much prominence recently. In general, neural networks are used as a predictive method, that is, their are used to estimate a regression function. ...
    • Estimação de funções do redshift de galáxias com base em dados fotométricos 

      Ferreira, Gretta Rossi (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 18/09/2017)
      In a substantial amount of astronomy problems, we are interested in estimating values assumed of some unknown quantity z ∈ R, for many function g, based on covariates x ∈ R^d. This is made using a sample (X1,Z1), ... ...
    • Quantificação em problemas com mudança de domínio 

      Vaz, Afonso Fernandes (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 17/05/2018)
      Several machine learning applications use classifiers as a way of quantifying the prevalence of positive class labels in a target dataset, a task named quantification. For instance, a naive way of determining what proportion ...
    • Vector representation of texts applied to prediction models 

      Stern, Deborah Bassi (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 09/03/2020)
      Natural Language Processing has gone through substantial changes over time. It was only recently that statistical approaches started receiving attention. The Word2Vec model is one of these. It is a shallow neural network ...
    • Conditional independence testing, two sample comparison and density estimation using neural networks 

      Inácio, Marco Henrique de Almeida (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 03/08/2020)
      Given the vast amount of data available nowadays and the rapid increase of computational processing power, the field of machine learning and the so called algorithmic modeling have seen a recent surge in its popularity and ...
    • Comparing two populations using Bayesian Fourier series density estimation 

      Inacio, Marco Henrique de Almeida (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 12/04/2017)
      Given two samples from two populations, one could ask how similar the populations are, that is, how close their probability distributions are. For absolutely continuous distributions, one way to measure the proximity of ...