Publications related to Smooth scheme

ALMOST SURE SCATTERING OF THE ENERGY-CRITICAL NLS IN d > 6

We study the energy-critical nonlinear Schrodinger equation with randomised initial data in dimensions d > 6. We prove that the Cauchy problem is almost surely globally well-posed with scattering for randomised supercritical initial data in H-s(Rd) wheneve ...

Springfield2023

Energy Bounds For A Fourth-Order Equation In Low Dimensions Related To Wave Maps

Tobias Johannes Schmid

For compact, isometrically embedded Riemannian manifolds N -> R-L, we introduce a fourth-order version of the wave maps equation. By energy estimates, we prove an a priori estimate for smooth local solutions in the energy subcritical dimension n = 1, 2. Th ...

AMER MATHEMATICAL SOC2022

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Continuous-Domain Formulation of Inverse Problems for Composite Sparse-Plus-Smooth Signals

Michaël Unser, Shayan Aziznejad, Thomas Jean Debarre

We present a novel framework for the reconstruction of 1D composite signals assumed to be a mixture of two additive components, one sparse and the other smooth, given a finite number of linear measurements. We formulate the reconstruction problem as a cont ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Fast Projection Onto Convex Smooth Constraints

Maryam Kamgarpour, Andreas Krause, Ilnura Usmanova

The Euclidean projection onto a convex set is an important problem that arises in numerous constrained optimization tasks. Unfortunately, in many cases, computing projections is computationally demanding. In this work, we focus on projection problems where ...

PMLR2021

A Multi-Agent Primal-Dual Strategy for Composite Optimization over Distributed Features

Ali H. Sayed, Sulaiman A S A E Alghunaim, Ming Yan

This work studies multi-agent sharing optimization problems with the objective function being the sum of smooth local functions plus a convex (possibly non-smooth) function coupling all agents. This scenario arises in many machine learning and engineering ...

IEEE2020

Hydraulic design of classical stilling basins downstream of stepped chutes

Anton Schleiss, Giovanni De Cesare, Michael Pfister, José Pedro Gamito de Saldanha Calado Matos, Ivan Stojnic

New design information regarding the hydraulic behaviour of classical stilling basins downstream of stepped chutes is presented and discussed. An extensive experimental campaign revealed that classical stilling basins preceded by stepped chutes cannot be a ...

2020

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Smooth scheme

ALMOST SURE SCATTERING OF THE ENERGY-CRITICAL NLS IN d > 6

A geographical study of (M)over-bar(2)(P-2, 4)(main)

Energy Bounds For A Fourth-Order Equation In Low Dimensions Related To Wave Maps

Wild solutions of the Navier-Stokes equations whose singular sets in time have Hausdorff dimension strictly less than 1

A first-order primal-dual method with adaptivity to local smoothness

Continuous-Domain Formulation of Inverse Problems for Composite Sparse-Plus-Smooth Signals

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Fast Projection Onto Convex Smooth Constraints

A Multi-Agent Primal-Dual Strategy for Composite Optimization over Distributed Features

Hydraulic design of classical stilling basins downstream of stepped chutes

Graph Chatbot

Chat with Graph Search

Wild solutions of the Navier-Stokes equations whose singular sets in time have Hausdorff dimension strictly less than 1

Energy Bounds For A Fourth-Order Equation In Low Dimensions Related To Wave Maps

Continuous-Domain Formulation of Inverse Problems for Composite Sparse-Plus-Smooth Signals

A geographical study of (M)over-bar(2)(P-2, 4)(main)

ALMOST SURE SCATTERING OF THE ENERGY-CRITICAL NLS IN d > 6

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Fast Projection Onto Convex Smooth Constraints

A Multi-Agent Primal-Dual Strategy for Composite Optimization over Distributed Features

A first-order primal-dual method with adaptivity to local smoothness

Hydraulic design of classical stilling basins downstream of stepped chutes