Maria Eduarda Pinheiro

Universal nonmonotone line search method for nonconvex multiobjective optimization problems with convex constraints

  • Maria Eduarda Pinheiro
  • Geovani Nunes Grapiglia
    • Categories Multi-Criteria Optimization Tags

    In this work we propose a general nonmonotone line-search method for nonconvex multi-objective optimization problems with convex constraints. At the \(k\)th iteration, the degree of nonmonotonicity is controlled by a vector \(\nu_{k}\) with nonnegative components. Different choices for \(\nu_{k}\) lead to different nonmonotone step-size rules. Assuming that the sequence \(\left\{\nu_{k}\right\}_{k\geq 0}\) is summable, and that … Read more

    Mixed-Integer Linear Optimization for Cardinality-Constrained Random Forests

  • Jan Pablo Burgard
  • Maria Eduarda Pinheiro
  • Martin Schmidt
    • Categories (Mixed) Integer Linear Programming, Optimization in Data Science Tags , , , ,

    Random forests are among the most famous algorithms for solving classification problems, in particular for large-scale data sets. Considering a set of labeled points and several decision trees, the method takes the majority vote to classify a new given point. In some scenarios, however, labels are only accessible for a proper subset of the given … Read more

    Mixed-Integer Linear Optimization for Semi-Supervised Optimal Classification Trees

  • Jan Pablo Burgard
  • Maria Eduarda Pinheiro
  • Martin Schmidt
    • Categories (Mixed) Integer Linear Programming, Optimization in Data Science Tags , ,

    Decision trees are one of the most famous methods for solving classification problems, mainly because of their good interpretability properties. Moreover, due to advances in recent years in mixed-integer optimization, several models have been proposed to formulate the problem of computing optimal classification trees. The goal is, given a set of labeled points, to split … Read more

    Mixed-Integer Quadratic Optimization and Iterative Clustering Techniques for Semi-Supervised Support Vector Machines

  • Martin Schmidt
  • Jan Pablo Burgard
  • Maria Eduarda Pinheiro
    • Categories (Mixed) Integer Nonlinear Programming, Data Science Algorithms, Data Science Applications Tags , , ,

    Among the most famous algorithms for solving classification problems are support vector machines (SVMs), which find a separating hyperplane for a set of labeled data points. In some applications, however, labels are only available for a subset of points. Furthermore, this subset can be non-representative, e.g., due to self-selection in a survey. Semi-supervised SVMs tackle … Read more