Publications associées à Unlocking crowding by ensemble statistics

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Youssef Allouah, Geovani Rizk

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Nicola Parolini, Ntorina Thanou, David Kraus, Andrea Kraus, Daniel Lopez, Markus Scholz, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Gaia Focused Product Release: Asteroid orbital solution: Properties and assessment

Stephan Morgenthaler, Shuangqing Liao

Context. We report the exploitation of a sample of Solar System observations based on data from the third Gaia Data Release (Gaia DR3) of nearly 157 000 asteroids. It extends the epoch astrometric solution over the time coverage planned for the Gaia DR4, w ...

Edp Sciences S A2023

A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation

Alexandre Caboussat, Dimitrios Gourzoulidis

We consider a least-squares/relaxation finite element method for the numerical solution of the prescribed Jacobian equation. We look for its solution via a least-squares approach. We introduce a relaxation algorithm that decouples this least-squares proble ...

SPRINGER/PLENUM PUBLISHERS2022

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

Nirupam Gupta

This paper considers the multi-agent linear least-squares problem in a server-agent network architecture. The system comprises multiple agents, each with a set of local data points. The agents are connected to a server, and there is no inter-agent communic ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Rapid Scalable Distributed Power Flow with Open-Source Implementation

Yuning Jiang, Xinliang Dai

This paper introduces a new method for solving the distributed AC power flow (PF) problem by further exploiting the problem formulation. We propose a new variant of the ALADIN algorithm devised specifically for this type of problem. This new variant is cha ...

ELSEVIER2022

High-Throughput Sizing, Counting, and Elemental Analysis of Anisotropic Multimetallic Nanoparticles with Single-Particle Inductively Coupled Plasma Mass Spectrometry

Natalia Gasilova, Andreas Züttel, Wen Luo, Mo Li, Cedric David Koolen, Ayush Agarwal

Nanoparticles (NPs) have wide applications in physical and chemical processes, and their individual properties (e.g., shape, size, and composition) and ensemble properties (e.g., distribution and homogeneity) can significantly affect the performance. Howev ...

2022

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

Jean-Philippe Thiran, Tobias Kober, Elda Fischi Gomez, Alessandro Daducci, Tom Hilbert, Elena Beanato, Gabriel Girard, Julia Brügger, Gian Franco Piredda, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Philipp Johannes Koch, Erick Jorge Canales Rodriguez, Marco Pizzolato, Andéol Geoffroy Cadic-Melchior, Thomas Yu, Chang-Hyun Park

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

2022

Superluminal Motion-Assisted Four-Dimensional Light-in-Flight Imaging

Edoardo Charbon, Kazuhiro Morimoto, Andrei Ardelean, Ming-Lo Wu

Advances in high-speed imaging techniques have opened new possibilities for capturing ultrafast phenomena such as light propagation in air or through media. Capturing light in flight in three-dimensional xyt space has been reported based on various types o ...

American Physical Society2021

Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems

Pascal Fua, Mathieu Salzmann, Fei Wang, Kwang Moo Yi, Zheng Dang, Yinlin Hu

Many classical Computer Vision problems, such as essential matrix computation and pose estimation from 3D to 2D correspondences, can be tackled by solving a linear least-square problem, which can be done by finding the eigenvector corresponding to the smal ...

IEEE COMPUTER SOC2021

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Aditya Vardhan Varre, Nicolas Henri Bernard Flammarion, Loucas Pillaud-Vivien

Motivated by the recent successes of neural networks that have the ability to fit the data perfectly \emph{and} generalize well, we study the noiseless model in the fundamental least-squares setup. We assume that an optimum predictor fits perfectly inputs ...

Advances in Neural Information Processing Systems 20212021

Charge fluctuations from molecular simulations in the constant-potential ensemble

Sara Bonella, Alessandro Coretti

We revisit the statistical mechanics of charge fluctuations in capacitors. In constant-potential classical molecular simulations, the atomic charges of electrode atoms are treated as additional degrees of freedom which evolve in time so as to satisfy the c ...

2020

Data assimilation of in situ and satellite remote sensing data to 3D hydrodynamic lake models: a case study using Delft3D-FLOW v4.03 and OpenDA v2.4

Alfred Johny Wüest, Damien Bouffard, Theo Baracchini

The understanding of physical dynamics is crucial to provide scientifically credible information on lake ecosystem management. We show how the combination of in situ observations, remote sensing data, and three-dimensional hydrodynamic (3D) numerical simul ...

2020

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections

Volkan Cevher, Junhong Lin

We study the least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space as a special case. We rst investigate regularized algorithms adapted to a projection operator on a closed subspace ...

2020

Local Vulnerabilities and Global Robustness of Coupled Dynamical Systems on Complex Networks

Melvyn Sandy Tyloo

Coupled dynamical systems are omnipresent in everyday life. In general, interactions between individual elements composing the system are captured by complex networks. The latter greatly impact the way coupled systems are functioning and evolving in time. ...

EPFL2020

Evaluation of Photocatalysts for Water Splitting through Combined Analysis of Surface Coverage and Energy-Level Alignment

Alfredo Pasquarello, Zhendong Guo, Francesco Ambrosio

To examine whether suitable conditions occur for the water splitting reaction at their interfaces with liquid water, we determine the pH-dependent surface coverage for a series of semiconductors, including GaAs, GaP, GaN, CdS, ZnO, SnO2, and rutile and ana ...

2020

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

Michele Ceriotti, Piero Gasparotto

A central paradigm of self-assembly is to create ordered structures starting from molecular monomers that spontaneously recognize and interact with each other via noncovalent interactions. In recent years, great efforts have been directed toward perfecting ...

AMER CHEMICAL SOC2020

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

Nicolas Macris, Mohamad Baker Dia, Jean François Emmanuel Barbier, Florent Gérard Krzakala

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections. A few examples where this problem is relevant are compressed sensing, sparse superposition codes, and code division multiple access. There has been a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Grand canonical simulations of electrochemical interfaces in implicit solvation models

Nicola Marzari, Oliviero Andreussi, Nicolas Georg Hörmann

We discuss grand canonical simulations based on density-functional theory to study the thermodynamic properties of electrochemical interfaces of metallic electrodes in aqueous environments. Water is represented using implicit solvation, here via the self-c ...

AMER INST PHYSICS2019

A new analysis approach for T-2 relaxometry myelin water quantification: Orthogonal Matching Pursuit

Guillaume Jean Op 't Veld

Purpose: In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T-2 relaxation is a powerful and widely appl ...

Wiley2019