Results 51 to 60 of about 1,319 (105)
Consensus-based optimisation with truncated noise
Consensus-based optimisation (CBO) is a versatile multi-particle metaheuristic optimisation method suitable for performing non-convex and non-smooth global optimisations in high dimensions.
Massimo Fornasier +3 more
doaj +1 more source
The unprecedented success of deep learning (DL) makes it unchallenged when it comes to classification problems. However, it is well established that the current DL methodology produces universally unstable neural networks (NNs).
Alexander Bastounis +2 more
doaj +1 more source
Accelerated Linearized Bregman Method [PDF]
In this paper, we propose and analyze an accelerated linearized Bregman (ALB) method for solving the basis pursuit and related sparse optimization problems.
Goldfarb, Donald, Huang, Bo, Ma, Shiqian
core +1 more source
Optimization applications of Goldbach's conjecture. [PDF]
Lin BMT, Lin SM, Shyu SJ.
europepmc +1 more source
Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks. [PDF]
Berrone S +3 more
europepmc +1 more source
A comprehensive view on optimization: reasonable descent [PDF]
Reasonable descent is a novel, transparent approach to a well-established field: the deep methods and applications of the complete analysis of continuous optimization problems.
Brinkhuis, J.
core +1 more source
A Simplified Convex Optimization Model for Image Restoration with Multiplicative Noise. [PDF]
Che H, Tang Y.
europepmc +1 more source
A fast continuous time approach with time scaling for nonsmooth convex optimization. [PDF]
Boţ RI, Karapetyants MA.
europepmc +1 more source
Time Rescaling of a Primal-Dual Dynamical System with Asymptotically Vanishing Damping. [PDF]
Hulett DA, Nguyen DK.
europepmc +1 more source
On the asymptotic behavior of the Douglas-Rachford and proximal-point algorithms for convex optimization. [PDF]
Banjac G, Lygeros J.
europepmc +1 more source

