5 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…
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…
A low-cost alternating projection approach for a continuous formulation of convex and cardinality constrained optimization
Nataša Krejić, Evelin H. M. Krulikovski, Marcos Raydan
We consider convex constrained optimization problems that also include a cardinality constraint. In general, optimization problems with cardinality constraints are difficult mathem…
Tax Evasion Risk Management Using a Hybrid Unsupervised Outlier Detection Method
Miloš Savić, Jasna Atanasijević, Dušan Jakovetić +1
Big data methods are becoming an important tool for tax fraud detection around the world. Unsupervised learning approach is the dominant framework due to the lack of label and grou…