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Concept

Absolute convergence

Related publications (28)

Adaptive Gradient Descent without Descent

We present a strikingly simple proof that two rules are sufficient to automate gradient descent: 1) don’t increase the stepsize too fast and 2) don’t overstep the local curvature. No need for functional values, no line search, no information about the func ...

2020

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections

Volkan Cevher, Junhong Lin

We study the least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space as a special case. We rst investigate regularized algorithms adapted to a projection operator on a closed subspace ...

2020

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Hubbard-corrected density functional perturbation theory with ultrasoft pseudopotentials

Nicola Marzari, Matteo Cococcioni, Iurii Timrov

We present in full detail a newly developed formalism enabling density functional perturbation theory (DFPT) calculations from a DFT + U ground state. The implementation includes ultrasoft pseudopotentials and is valid for both insulating and metallic syst ...

AMER PHYSICAL SOC2020

A construction of the Stable Web

Thomas Mountford

We provide a process on the space of collections of coalescing cadlag stable paths and show convergence in an appropriate topology for coalescing stable random walks on the integer lattice. ...

IMPA2019

Exploring The Borderlands Of The Gathering Problem

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer

Problems of pattern formation have been extensively studied in distributed computing. One of this problems is the gathering problem: agents must gather at a same position in a distributed manner. When gathering is not possible, a close problem is the conve ...

2019

An Inertial Parallel and Asynchronous Forward-Backward Iteration for Distributed Convex Optimization

Colin Neil Jones, Georgios Stathopoulos

Two characteristics that make convex decomposition algorithms attractive are simplicity of operations and generation of parallelizable structures. In principle, these schemes require that all coordinates update at the same time, i.e., they are synchronous ...

SPRINGER/PLENUM PUBLISHERS2019

A local discontinuous Galerkin gradient discretization method for linear and quasilinear elliptic equations

Assyr Abdulle, Giacomo Rosilho De Souza

A local weighted discontinuous Galerkin gradient discretization method for solving elliptic equations is introduced. The local scheme is based on a coarse grid and successively improves the solution solving a sequence of local elliptic problems in high gra ...

EDP SCIENCES S A2019