24 citations · 26 across the 7 of their papers we have counts for
11 papers
A Projected Stochastic Gradient Method for Finite-Sum Problems with Linear Equality Constraints
Natasa Krklec Jerinkic, Benedetta Morini, Mahsa Yousefi
A stochastic gradient method for finite-sum minimization subject to deterministic linear constraints is proposed and analyzed. The procedure presented adapts the projected gradient…
AS-BOX: Additional Sampling Method for Weighted Sum Problems with Box Constraints
Nataša Krejić, Nataša Krklec Jerinkić, Tijana Ostojić +1
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 meth…
A Hessian inversion-free exact second order method for distributed consensus optimization
Dusan Jakovetic, Natasa Krejic, Natasa Krklec Jerinkic
We consider a standard distributed consensus optimization problem where a set of agents connected over an undirected network minimize the sum of their individual local strongly con…
An inexact restoration-nonsmooth algorithm with variable accuracy for stochastic nonsmooth convex optimization problems in machine learning and stochastic linear complementarity problems
Natasa Krejic, Natasa Krklec Jerinkic, Tijana Ostojic
We study unconstrained optimization problems with nonsmooth and convex objective function in the form of a mathematical expectation. The proposed method approximates the expected o…
Emotion pattern detection on facial videos using functional statistics
Rongjiao Ji, Alessandra Micheletti, Natasa Krklec Jerinkic +1
There is an increasing scientific interest in automatically analysing and understanding human behavior, with particular reference to the evolution of facial expressions and the rec…
Distributed Fixed Point Method for Solving Systems of Linear Algebraic Equations
Dusan Jakovetic, Natasa Krejic, Natasa Krklec Jerinkic +2
We present a class of iterative fully distributed fixed point methods to solve a system of linear equations, such that each agent in the network holds one of the equations of the s…
Exact Spectral-Like Gradient Method for Distributed Optimization
Dusan Jakovetic, Natasa Krejic, Natasa Krklec Jerinkic
Since the initial proposal in the late 80s, spectral gradient methods continue to receive significant attention, especially due to their excellent numerical performance on various…
Subsampled Nonmonotone Spectral Gradient Methods
Stefania Bellavia, Nataša Krklec Jerinkić, Greta Malaspina
This paper deals with subsampled spectral gradient methods for minimizing finite sum. Subsample function and gradient approximations are employed in order to reduce the overall com…
Distributed second order methods with increasing number of working nodes
Natasa Krklec Jerinkic, Dusan Jakovetic, Natasa Krejic +1
Recently, an idling mechanism has been introduced in the context of distributed \emph{first order} methods for minimization of a sum of nodes' local convex costs over a generic, co…
Newton-like method with diagonal correction for distributed optimization
Dragana Bajovic, Dusan Jakovetic, Natasa Krejic +1
We consider distributed optimization problems where networked nodes cooperatively minimize the sum of their locally known convex costs. A popular class of methods to solve these pr…
Distributed Gradient Methods with Variable Number of Working Nodes
Dusan Jakovetic, Dragana Bajovic, Natasa Krejic +1
We consider distributed optimization where nodes in a connected network minimize the sum of their local costs subject to a common constraint set. We propose a distributed proje…