6 papers
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…
EFIX: Exact Fixed Point Methods for Distributed Optimization
Dusan Jakovetic, Natasa Krejic, Natasa Krklec Jerinkic
We consider strongly convex distributed consensus optimization over connected networks. EFIX, the proposed method, is derived using quadratic penalty approach. In more detail, we u…
Detection of Iterative Adversarial Attacks via Counter Attack
Matthias Rottmann, Kira Maag, Mathis Peyron +2
Deep neural networks (DNNs) have proven to be powerful tools for processing unstructured data. However for high-dimensional data, like images, they are inherently vulnerable to adv…
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…
Inexact restoration with subsampled trust-region methods for finite-sum minimization
Stefania Bellavia, Natasa Krejic, Benedetta Morini
Convex and nonconvex finite-sum minimization arises in many scientific computing and machine learning applications. Recently, first-order and second-order methods where objective f…
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…