Abstract: We consider the problem of decentralized consensus optimization, where the sum of n smooth and strongly convex functions are minimized over n distributed agents that form a connected network ...

Function secret sharing (FSS) is a secret sharing technique for functions in a specific function class, mainly including distributed point function (DPF) and distributed comparison function (DCF). As ...

pwtools is a Python package for pre- and postprocessing of atomistic calculations, mostly targeted to Quantum Espresso, CPMD, CP2K and LAMMPS. It is almost, but not quite, entirely unlike ASE, with ...

Abstract: Aitken gradient descent (AGD) algorithm takes some advantages over the standard gradient descent and Newton methods: 1) can achieve at least quadratic convergence in general; 2) does not ...

We introduce the Tensor-Based Multivariate Optimization (TeMPO) framework for use in nonlinear optimization problems commonly encountered in signal processing, machine learning, and artificial ...

The Rosenbrock function optimization belongs to unconstrained optimization problems, and its global minimum value is located at the bottom of a smooth and narrow valley of the parabolic shape. It is ...

Stochastic gradient descent (SGD) is pivotal in solving optimisation problems within deep learning. SGD utilises random subsets of data to compute gradients, enhancing its effectiveness for non-convex ...