Publications related to Convergence analysis of Padé approximations for Helmholtz frequency response problems

Distributional Regression and Autoregression via Optimal Transport

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Outlier-free spline spaces for isogeometric discretizations of biharmonic and polyharmonic eigenvalue problems

Espen Sande

We present outlier-free isogeometric Galerkin discretizations of eigenvalue problems related to the biharmonic and the polyharmonic operator in the univariate setting. These are Galerkin discretizations in certain spline subspaces that provide accurate app ...

Lausanne2023

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

Tobias Kippenberg, Rui Ning Wang, Xinru Ji, Zheru Qiu, Junqiu Liu, Jijun He

We implement Euler bends to build compact high-Q Si3N4 racetrack microresonators, featuring a small footprint of only 0.21 mm(2) for 19.8 GHz FSR. We demonstrate that these multi-mode microresonators can be operated in the single-mode regime and generate a ...

IEEE2022

Estimate on the Dimension of the Singular Set of the Supercritical Surface Quasigeostrophic Equation

Maria Carola Colombo, Silja Noëmi Aline Haffter

We consider the SQG equation with dissipation given by a fractional Laplacian of order α

2021

A combinatorial proof of a sumset conjecture of Furstenberg

Florian Karl Richter

We give a new proof of a sumset conjecture of Furstenberg that was first proved by Hochman and Shmerkin in 2012: if

\log r / \log s

is irrational and

X

and

Y

are

\times r

- and

\times s

-invariant subsets of

[0,1]

, respectively, then $\dim_\text{ ...

2021

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Volkan Cevher, Ali Kavis, Shaul Nadav Hallak

This paper analyzes the trajectories of stochastic gradient descent (SGD) to help understand the algorithm’s convergence properties in non-convex problems. We first show that the sequence of iterates generated by SGD remains bounded and converges with prob ...

2020

Log Barriers for Safe Non-convex Black-box Optimization

Maryam Kamgarpour, Andreas Krause, Ilnura Usmanova

We address the problem of minimizing a smooth function f0(x) over a compact set D defined by smooth functional constraints fi(x)≤0, i=1,…,m given noisy value measurements of fi(x). This problem arises in safety-critical applications, where certain paramete ...

2019

Penalization and Bayesian numerical methods for multiscale inverse problems

Andrea Di Blasio

In this thesis we consider inverse problems involving multiscale elliptic partial differential equations. The name multiscale indicates that these models are characterized by the presence of parameters which vary on different spatial scales (macroscopic, m ...

EPFL2019

Convergence Of Variance-Reduced Learning Under Random Reshuffling

Ali H. Sayed, Bicheng Ying, Kun Yuan

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizers. The existing convergence results assume uniform ...

IEEE2018

Convergence analysis of Padé approximations for Helmholtz frequency response problems

Graph Chatbot

Chat with Graph Search

Distributional Regression and Autoregression via Optimal Transport

Outlier-free spline spaces for isogeometric discretizations of biharmonic and polyharmonic eigenvalue problems

Localization errors of the stochastic heat equation

Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

Estimate on the Dimension of the Singular Set of the Supercritical Surface Quasigeostrophic Equation

A combinatorial proof of a sumset conjecture of Furstenberg

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Log Barriers for Safe Non-convex Black-box Optimization

Penalization and Bayesian numerical methods for multiscale inverse problems

Convergence Of Variance-Reduced Learning Under Random Reshuffling

Localization errors of the stochastic heat equation

Distributional Regression and Autoregression via Optimal Transport

Outlier-free spline spaces for isogeometric discretizations of biharmonic and polyharmonic eigenvalue problems

Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

Penalization and Bayesian numerical methods for multiscale inverse problems

Convergence Of Variance-Reduced Learning Under Random Reshuffling

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Log Barriers for Safe Non-convex Black-box Optimization

Estimate on the Dimension of the Singular Set of the Supercritical Surface Quasigeostrophic Equation

A combinatorial proof of a sumset conjecture of Furstenberg