Now showing items 1-13 of 13

    • Cifrado de imágenes y Matemáticas 

      Rojas, Ángela; Cano, Alberto (Universidad Nacional de La Plata, 2011)
      Un tema que debe interesar al profesorado de Matemáticas de todos los niveles educativos es cómo hacer comprender a nuestros alumnos la utilidad de los conceptos matemáticos que están estudiando en nuestras asignaturas. ...
    • Una clase de aritmética modular, matrices y cifrado para Ingeniería 

      Rojas, Ángela; Cano, Alberto (Federación Iberoamericana de Educación Matemática (FISEM), 2011)
      El Álgebra Lineal tiene una gran cantidad de aplicaciones sin embargo se suele abordar casi siempre de una forma bastante abstracta a nivel universitario. Así que para motivar a nuestro alumnado planificamos realizar ...
    • A Classification Module for Genetic Programming Algorithms in JCLEC 

      Cano, Alberto; Luna, J.M.; Zafra, Amelia; Ventura Soto, S. (MIT Press, 2014)
      JCLEC-Classi cation is a usable and extensible open source library for genetic program- ming classi cation algorithms. It houses implementations of rule-based methods for clas- si cation based on genetic programming, ...
    • Classification Rule Mining with Iterated Greedy 

      Pedraza, Juan A.; García-Martínez, Carlos; Cano, Alberto; Ventura Soto, S. (2017-03-30)
      In the context of data mining, classi cation rule discovering is the task of designing accurate rule based systems that model the useful knowledge that di erentiate some data classes from others, and is present in large ...
    • JCLEC Meets WEKA! 

      Cano, Alberto; Luna, J.M.; Olmo Ortiz, Juan Luis; Ventura Soto, S. (2014-02-27)
      WEKA has recently become a very referenced DM tool. In spite of all the functionality it provides, it does not include any framework for the development of evolutionary algorithms. An evolutionary computation framework ...
    • Multi-Objective Genetic Programming for Feature Extraction and Data Visualization 

      Cano, Alberto; Ventura Soto, S.; Cios, Krzyztof J. (2017-03-31)
      Feature extraction transforms high dimensional data into a new subspace of lower dimensionalitywhile keeping the classification accuracy. Traditional algorithms do not consider the multi-objective nature of this task. ...
    • Parallel evaluation of Pittsburgh rule-based classifiers on GPUs 

      Cano, Alberto; Zafra, Amelia; Ventura Soto, S. (2017-01-19)
      Individuals from Pittsburgh rule-based classifiers represent a complete solution to the classification problem and each individual is a variable-length set of rules. Therefore, these systems usually demand a high level ...
    • Parallelization Strategies for Markerless Human Motion Capture 

      Cano, Alberto; Yeguas-Bolivar, Enrique; Medina-Carnicer, R.; Ventura Soto, S.; Muñoz-Salinas, Rafael (2015-10-15)
      Markerless Motion Capture (MMOCAP) is the problem of determining the pose of a person from images captured by one or several cameras simultaneously without using markers on the subject. Evaluation of the solutions is ...
    • Scalable CAIM Discretization on Multiple GPUs Using Concurrent Kernels 

      Cano, Alberto; Ventura Soto, S.; Cios, Krzysztof J. (2017-01-19)
      CAIM(Class-Attribute InterdependenceMaximization) is one of the stateof- the-art algorithms for discretizing data for which classes are known. However, it may take a long time when run on high-dimensional large-scale ...
    • Speeding Up Evolutionary Learning Algorithms using GPUs 

      Cano, Alberto; Zafra, Amelia; Ventura Soto, S. (ESTYLF, 2010)
      This paper propose a multithreaded Genetic Programming classi cation evaluation model using NVIDIA CUDA GPUs to reduce the computational time due to the poor perfor- mance in large problems. Two di erent clas- si ...
    • Speeding up Multiple Instance Learning Classification Rules on GPUs 

      Cano, Alberto; Zafra, Amelia; Ventura Soto, S. (2017-01-19)
      Multiple instance learning is a challenging task in supervised learning and data mining. How- ever, algorithm performance becomes slow when learning from large-scale and high-dimensional data sets. Graphics processing ...
    • Trabajando con imágenes digitales en clase de Matemáticas 

      Rojas, Ángela; Cano, Alberto (Real Sociedad Matemática Española, 2010)
    • ur-CAIM: Improved CAIM Discretization for Unbalanced and Balanced Data 

      Cano, Alberto; Nguyen, Dat T.; Ventura Soto, S.; Cios, Krzysztof J. (2015-10-15)
      Supervised discretization is one of basic data preprocessing techniques used in data mining. CAIM (Class- Attribute InterdependenceMaximization) is a discretization algorithm of data for which the classes are known. ...