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Concept

Smooth scheme

Related publications (28)

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study

Dimitri Nestor Alice Van De Ville, Patric Hagmann, Maria Giulia Preti

Objective: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). ...

ELSEVIER IRELAND LTD2023

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

Katie Sabrina Catherine Rosie Marsden

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 ...

Amer Inst Mathematical Sciences-Aims2023

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

Francesca Carocci

We discuss criteria for a stable map of genus two and degree 4 to the projective plane to be smoothable, as an application of our modular desingularisation of (M) over bar (2,n)(P-r, d)(main) via logarithmic geometry and Gorenstein singularities. ...

WALTER DE GRUYTER GMBH2022

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 ...

American Mathematical Society (AMS)2022

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

Maria Colombo

We prove non-uniqueness for a class of weak solutions to the Navier???Stokes equations which have bounded kinetic energy, integrable vorticity, and are smooth outside a fractal set of singular times with Hausdorff dimension strictly less than 1. ...

2022

Spectral analysis for transmission eigenvalue problems with and without the complementing conditions

Jean Louis-Alexandre Fornerod

The interior transmission eigenvalue problem is a system of partial differential equations equipped with Cauchy data on the boundary: the transmission conditions. This problem appears in the inverse scattering theory for inhomogeneous media when, for some ...

EPFL2022

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 ...

2021

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

On Linear Interpolation in the Latent Space of Deep Generative Models

Quentin Christian Becker

The underlying geometrical structure of the latent space in deep generative models is in most cases not Euclidean, which may lead to biases when comparing interpolation capabilities of two models. Smoothness and plausibility of linear interpolations in lat ...

2021

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

Ali H. Sayed, Sulaiman A S A E Alghunaim

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

A critically degenerate elliptic Dirichlet problem, spectral theory and bifurcation

Charles Stuart

In an open, bounded subset Omega of R-N such that 0 is an element of Omega we consider the nonlinear eigenvalue problem -Sigma(N)(i,j,=1) partial derivative(i){A(ij)(x)partial derivative(j)u} + V(x)u + n(x,del u)+ g(x, u) = lambda u in Omega integral(Omega ...

2020

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

A Study of Several Artificial Viscosity Models within the Discontinuous Galerkin Framework

Jan Sickmann Hesthaven

Dealing with strong shocks while retaining low numerical dissipation traditionally has been one of the major challenges for high order methods like discontinuous Galerkin (DG). In the literature, shock capturing models have been designed for DG based on va ...

GLOBAL SCIENCE PRESS2020

Birational characterization of abelian varieties and ordinary abelian varieties in characteristic p>0

Lei Zhang, Zsolt Patakfalvi

Let k be an algebraically closed field of characteristic p > 0. We give a birational characterization of ordinary abelian varieties over k: a smooth projective variety X is birational to an ordinary abelian variety if and only if kappa(S)(X) = 0 and b(1)(X ...

DUKE UNIV PRESS2019

The sources of sovereign risk: a calibration based on Levy stochastic processes

Sylvain Jean Pascal Carré

Governments choose to issue risky or riskless debt depending on the nature of the stochastic process of output. We use Brownian motion and Poisson shocks a modeling method in the literature on corporate default known as Levy processes to approximate a deco ...

ELSEVIER SCIENCE BV2019

On subadditivity of Kodaira dimension in positive characteristic over a general type base

Zsolt Patakfalvi

We show that for a surjective, separable morphism f of smooth projective varieties over a field of positive characteristic such that f(*) OX congruent to O-Y subadditivity of Kodaira dimension holds, provided the base is of general type and the Hasse-Witt ...

2018

Distributed Inference over Multitask Graphs under Smoothness

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This paper formulates a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. The smoothness requirement softens the tra ...

IEEE2018

Related publications (28)

Scalable constrained optimization

Maria-Luiza Vladarean

EPFL2024

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study

Dimitri Nestor Alice Van De Ville, Patric Hagmann, Maria Giulia Preti

ELSEVIER IRELAND LTD2023

\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