Additional sampling

AS-BOX: Additional Sampling Method for Weighted Sum Problems with Box Constraints

  • Nataša Krejić
  • Nataša Krklec Jerinkić
  • Tijana Ostojić
  • Nemanja Vučićević
    • Categories Bound-constrained Optimization, Nonlinear Optimization Tags , , , , ,

    A class of optimization problems characterized by a weighted finite-sum objective function subject to box constraints is considered. We propose a novel stochastic optimization method, named AS-BOX (Additional Sampling for BOX constraints), that combines projected gradient directions with adaptive variable sample size strategies and nonmonotone line search. The method dynamically adjusts the batch size based … Read more

    ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints

  • Nataša Krejić
  • Nataša Krklec Jerinkić
  • Tijana Ostojić
  • Nemanja Vučićević
    • Categories Nonlinear Optimization, Stochastic Approaches, Stochastic Programming Tags , , , , , ,

    We propose a novel algorithm for solving non-convex, nonlinear equality-constrained finite-sum optimization problems. The proposed algorithm incorporates an additional sampling strategy for sample size update into the well-known framework of quadratic penalty methods. Thus, depending on the problem at hand, the resulting method may exhibit a sample size strategy ranging from a mini-batch on one … Read more

    ASMOP: Additional sampling stochastic trust region method for multi-objective problems

  • Nataša Krklec Jerinkić
  • Luka Rutešić
    • Categories Multi-Criteria Optimization, Optimization of Systems modeled by PDEs, Stochastic Programming Tags , , , , ,

    We consider an unconstrained multi-criteria optimization problem with finite sum objective functions. The proposed algorithm belongs to a non-monotone trust-region framework where additional sampling approach is used to govern the sample size and the acceptance of a candidate point. Depending on the problem, the method can result in a mini-batch or an increasing sample size … Read more

    IPAS: An Adaptive Sample Size Method for Weighted Finite Sum Problems with Linear Equality Constraints

  • Nataša Krejić
  • Nataša Krklec Jerinkić
  • Sanja Rapajić
  • Luka Rutešić
    • Categories Constrained Nonlinear Optimization, Stochastic Programming Tags , , , , ,

    Optimization problems with the objective function in the form of weighted sum and linear equality constraints are considered. Given that the number of local cost functions can be large as well as the number of constraints, a stochastic optimization method is proposed. The method belongs to the class of variable sample size first order methods, … Read more

    Variable metric proximal stochastic gradient methods with additional sampling

  • Ilaria Trombini
  • Federica Porta
  • Nataša Krklec Jerinkić
  • Valeria Ruggiero
    • Categories Stochastic Approaches Tags , , ,

    Regularized empirical risk minimization problems arise in a variety of applications, including machine learning, signal processing, and image processing. Proximal stochastic gradient algorithms are a standard approach to solve these problems due to their low computational cost per iteration and a relatively simple implementation. This paper introduces a class of proximal stochastic gradient methods built … Read more