6 papers
ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
Nataša Krejić, Nataša Krklec Jerinkić, Tijana Ostojić +1
We propose a novel algorithm for solving non-convex, nonlinear equality-constrained finite-sum optimization problems. The proposed algorithm incorporates an additional sampling str…
ASMOP: Additional sampling stochastic trust region method for multi-objective problems
Nataša Krklec Jerinkić, Luka Rutešić, Ilaria Trombini
We consider unconstrained multi-criteria optimization problems with finite sum objective functions. The proposed algorithm belongs to a non-monotone trust region framework where ad…
IPAS: An Adaptive Sample Size Method for Weighted Finite Sum Problems with Linear Equality Constraints
Nataša Krejić, Nataša Krklec Jerinkić, Sanja Rapajić +1
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 l…
SMOP: Stochastic trust region method for multi-objective problems
Nataša Krejić, Nataša Krklec Jerinkić, Luka Rutešić
The problem we consider is a multi-objective optimization problem, in which the goal is to find an optimal value of a vector function representing various criteria. The aim of this…
AN-SPS: Adaptive Sample Size Nonmonotone Line Search Spectral Projected Subgradient Method for Convex Constrained Optimization Problems
Nataša Krklec Jerinkić, Tijana Ostojić
We consider convex optimization problems with a possibly nonsmooth objective function in the form of a mathematical expectation. The proposed framework (AN-SPS) employs Sample Aver…
Group pattern detection of longitudinal data using functional statistics
Rongjiao Ji, Alessandra Micheletti, Nataša Krklec Jerinkić +1
Estimations and evaluations of the main patterns of time series data in groups benefit large amounts of applications in various fields. Different from the classical auto-correlatio…