Concept

Moyenne géométrique

Publications associées (83)

Strain-based analysis on the influence of local undercut geometry on fatigue crack initiation life

Alain Nussbaumer, Heikki Tapani Remes, Abinab Niraula

The local undercut defects at the weld toe provide a potential initiation site for fatigue cracks and significantly impact the structure's fatigue strength. The influence of continuous undercut depth on fatigue performance is widely studied, but the resear ...

2024

On the Fusion Strategies for Federated Decision Making

Ali H. Sayed, Emre Telatar, Mert Kayaalp, Yunus Inan

We consider the problem of information aggregation in federated decision making, where a group of agents collaborate to infer the underlying state of nature without sharing their private data with the central processor or each other. We analyze the non-Bay ...

2023

Divertor detachment and reattachment with mixed impurity seeding on ASDEX Upgrade

Using newly developed spectroscopic models to measure the divertor concentration of Ne and Ar, it is shown that the experimental detachment threshold on ASDEX Upgrade with Ar-only and mixtures of Ar+N or Ne+N scales as expected in comparison with an analyt ...

IOP Publishing Ltd2023

Grassmannian diffusion maps based surrogate modeling via geometric harmonics

A novel surrogate model based on the Grassmannian diffusion maps (GDMaps) and utilizing geometric harmonics (GH) is developed for predicting the response of complex physical phenomena. The method utilizes GDMaps to obtain a low-dimensional representation o ...

2022

Robots' Motion Planning in Human Crowds by Acceleration Obstacles

Aude Billard, Diego Felipe Paez Granados, David Julian Gonon

We study the Acceleration Obstacle (AO) as a concept to enable a robot's navigation in human crowds. The AO's geometric properties are analyzed and a direct sampling-free algorithm is proposed to approximate its boundary by linear constraints. The resultin ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Wasserstein Adversarial Regularization for learning with label noise

Devis Tuia, Sylvain Lobry, Nicolas Courty

Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we propose ...

2021

An implicit split-operator algorithm for the nonlinear time-dependent Schrödinger equation

Jiri Vanicek, Julien Roulet

The explicit split-operator algorithm is often used for solving the linear and nonlinear time-dependent Schrödinger equations. However, when applied to certain nonlinear time-dependent Schrödinger equations, this algorithm loses time reversibility and seco ...

2021

Affine Combination of Diffusion Strategies Over Networks

Ali H. Sayed, Jie Chen

Diffusion adaptation is a powerful strategy for distributed estimation and learning over networks. Motivated by the concept of combining adaptive filters, this work proposes a combination framework that aggregates the operation of multiple diffusion strate ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Variance-Reduced Stochastic 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 minimizer. The existing convergence results assume uniform d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Finite beta effects on short wavelength ion temperature gradient modes

Laurent Villard

The electromagnetic effect is studied on the short wavelength branch of the ion temperature gradient mode in the linear regime for the first time using a global gyrokinetic model. The short wavelength ion temperature gradient mode growth rate is found to b ...

2020

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