Publications related to Generalized minimal residual method

Recompression Of Hadamard Products Of Tensors In Tucker Format

The Hadamard product features prominently in tensor-based algorithms in scientific computing and data analysis. Due to its tendency to significantly increase ranks, the Hadamard product can represent a major computational obstacle in algorithms based on lo ...

Siam Publications2017

Exact diffusion strategy for optimization by networked agents

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work develops a distributed optimization algorithm with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown to have a wider stability range and superior convergence pe ...

IEEE2017

Exact Diffusion for Distributed Optimization and Learning---Part I: Algorithm Development

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work develops a distributed optimization strategy with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown in Part II to have a wider stability range and superior conv ...

2017

A matrix DEIM technique for model reduction of nonlinear parametrized problems in cardiac mechanics

Alfio Quarteroni, Andrea Manzoni

When relying on Newton iterations to solve nonlinear problems in the context of Reduced Basis (RB) methods, the assembling of the RB arrays during the online stage depends on the dimension of the underlying high-fidelity approximation. This is more of an i ...

Elsevier Science Sa2017

Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval

Volkan Cevher, Quoc Tran Dinh, Alp Yurtsever, Yen-Huan Li, Ya-Ping Hsieh, Marwa El Halabi, Gergely Odor

We study a phase retrieval problem in the Poisson noise model. Motivated by the PhaseLift approach, we approximate the maximum-likelihood estimator by solving a convex program with a nuclear norm constraint. While the Frank-Wolfe algorithm, together with t ...

Ieee2016

MATHICSE Technical Report : A matrix discrete empirical interpolation method for the efficient model reduction of parametrized nonlinear PDEs: application to nonlinear elasticity problems

Alfio Quarteroni, Andrea Manzoni

When using Newton iterations to solve nonlinear parametrized PDEs in the context of Reduced Basis (RB)methods, the assembling of the RB arrays in the online stage depends in principle on the high-fidelityapproximation. This task is even more challenging wh ...

MATHICSE2016

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

Pierre Vandergheynst, Daniel Kressner, Nathanaël Perraudin, Ana Susnjara

Sinal-processing on graphs has developed into a very active field of research during the last decade. In particular, the number of applications using frames con-structed from graphs, like wavelets on graphs, has substantially increased. To attain scalabili ...

MATHICSE2015

MATHICSE Technical Report : Semi-implicit BDF time discretization of the Navier-Stokes equations with VMS-LES modeling in a High Performance Computing framework

Luca Dede', Davide Forti

In this paper, we propose a semi–implicit approach for the time discretization of the Navier–Stokes equations with Variational Multiscale–Large Eddy Simulation turbulence modeling (VMS–LES). For the spatial approximation of the problem, we use the Finite E ...

MATHICSE2015

A Comparison of Preconditioners for the Steklov–Poincaré Formulation of the Fluid-Structure Coupling in Hemodynamics

Alfio Quarteroni, Simone Deparis, Davide Forti

A Fluid–Structure Interaction (FSI) problem can be reinterpreted as a heterogeneous problem with two subdomains. It is possible to describe the coupled problem at the interface between the fluid and the structure, yielding a nonlinear Steklov–Poincaré prob ...

2015

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Generalized minimal residual method

Recompression Of Hadamard Products Of Tensors In Tucker Format

Exact diffusion strategy for optimization by networked agents

Exact Diffusion for Distributed Optimization and Learning---Part I: Algorithm Development

A matrix DEIM technique for model reduction of nonlinear parametrized problems in cardiac mechanics

Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval

MATHICSE Technical Report : A matrix discrete empirical interpolation method for the efficient model reduction of parametrized nonlinear PDEs: application to nonlinear elasticity problems

Semi-implicit BDF time discretization of the Navier–Stokes equations with VMS-LES modeling in a High Performance Computing framework

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

MATHICSE Technical Report : Semi-implicit BDF time discretization of the Navier-Stokes equations with VMS-LES modeling in a High Performance Computing framework

A Comparison of Preconditioners for the Steklov–Poincaré Formulation of the Fluid-Structure Coupling in Hemodynamics

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A matrix DEIM technique for model reduction of nonlinear parametrized problems in cardiac mechanics

Recompression Of Hadamard Products Of Tensors In Tucker Format

Semi-implicit BDF time discretization of the Navier–Stokes equations with VMS-LES modeling in a High Performance Computing framework

Exact Diffusion for Distributed Optimization and Learning---Part I: Algorithm Development

Exact diffusion strategy for optimization by networked agents

Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval

MATHICSE Technical Report : A matrix discrete empirical interpolation method for the efficient model reduction of parametrized nonlinear PDEs: application to nonlinear elasticity problems

MATHICSE Technical Report : Semi-implicit BDF time discretization of the Navier-Stokes equations with VMS-LES modeling in a High Performance Computing framework

A Comparison of Preconditioners for the Steklov–Poincaré Formulation of the Fluid-Structure Coupling in Hemodynamics

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method