• Análise posicional de jogadores brasileiros de futebol utilizando dados GPS 

      Gasparini, Randal (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC-So, Câmpus Sorocaba, 26/02/2018)
      The professional soccer is always changing and is constantly searching tools and data to help the decision-making, providing tatics and techniques to the team. In Brazil, this sport goes to same way and the investiments ...
    • 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 ...
    • On the training algorithms for Restricted Boltzmann Machine-Based Models 

      Passos Junior, Leandro Aparecido (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 05/12/2018)
      Deep learning techniques have been studied extensively in the last years, due to its good results related to essential tasks on a large range of applications, such as speech and face recognition, as well as objects ...
    • Classificação de retornos utilizando dados de alta frequência no mercado de bitcoins 

      Emílio, João Mateus Arcolini (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 10/03/2020)
      In the cryptocurrency market, Bitcoin stands out as the most accepted traded in the world. However, due to its high volatility, the prediction of price behaviors, in special, the trend classification, becomes a challenge ...
    • ML-MDLText: um método de classificação de textos multirrótulo de aprendizado incremental 

      Bittencourt, Marciele de Menezes (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC-So, Câmpus Sorocaba, 27/03/2020)
      Single-label text classification has been extensively studied in the last decades and usually more attention has been given to offline learning scenarios, where all of the training data is available in advance. However, ...
    • On the advances in pattern recognition using Optimum-Path Forest 

      Sugi Afonso, Luis Claudio (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 24/09/2020)
      Pattern recognition (PR) techniques have been paramount to solve different and complex problems in many fields of study. The basic idea behind PR techniques is to compute a model capable of classifying unknown samples. ...