Publications associées à Fraction (mathématiques)

Robust Sparse Voting

Rachid Guerraoui, Youssef Allouah, Oscar Jean Olivier Villemaud, Le Nguyen Hoang

Many applications, such as content moderation and recommendation, require reviewing and scoring a large number of alternatives. Doing so robustly is however very challenging. Indeed, voters' inputs are inevitably sparse: most alternatives are only scored b ...

2024

Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity

Athanasios Nenes, Spyros Pandis

This study explores the differences in performance and results by various versions of the ISORROPIA thermodynamic module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Three different versions of the module were used, ISORROPIA II v ...

Copernicus Gesellschaft Mbh2024

Cooperative Concurrency Control for Write-Intensive Key-Value Workloads

Babak Falsafi, Alexandros Daglis, Mark Johnathon Sutherland

Key-Value Stores (KVS) are foundational infrastructure components for online services. Due to their latency-critical nature, today’s best-performing KVS contain a plethora of full-stack optimizations commonly targeting read-mostly, popularity-skewed worklo ...

ACM2023

Single fraction and hypofractionated radiosurgery for perioptic meningiomas-tumor control and visual outcomes: a systematic review and meta-analysis

Constantin Tuleasca

Perioptic meningiomas, defined as those that are less than 3 mm from the optic apparatus, are challenging to treat with stereotactic radiosurgery (SRS). Tumor control must be weighed against the risk of radiation-induced optic neuropathy (RION), as both tu ...

Springer2023

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, John Stephan, Sadegh Farhadkhani, Le Nguyen Hoang, Nirupam Gupta, Rafaël Benjamin Pinot

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023

Phase Transformation-Induced Interfacial Debonding of Silica Inclusions in Iron

Andreas Mortensen, David Hernandez Escobar, Julie Nathalie S Gheysen, Alejandra Inés Slagter

We document that in unstressed, undeformed, samples of pure iron containing silica inclusions precipitated by melt deoxidation, the iron matrix and a small fraction of the silica inclusions are locally separated at room temperature by a void. Thermal cycli ...

Springer2023

Facets of Urban Co-Creation

Roberto Sega

Participation in the context of urban planning is growing in the urban and architectural processes of democratic cities. Urban co-creation means working with communities by integrating their needs, giving them the opportunity to collaborate in the transfor ...

Univ Politecnica Catalunya2023

Metallicity Distribution Functions of 13 Ultra-faint Dwarf Galaxy Candidates from Hubble Space Telescope Narrowband Imaging

Nicolas Lawrence Etienne Longeard

We present uniformly measured stellar metallicities of 463 stars in 13 Milky Way (MW) ultra-faint dwarf galaxies (UFDs; M-V = -7.1 to -0.8) using narrowband CaHK (F395N) imaging taken with the Hubble Space Telescope. This represents the largest homogeneous ...

Iop Publishing Ltd2023

Sporadic type VI secretion in seventh pandemic Vibrio cholerae

Melanie Blokesch, Sandrine Stutzmann, Nicolas René Chiaruttini, Alexis Joseph Proutière, Loriane Bader, Lisa Christina Metzger, Natalia Carolina Drebes Dorr, Sandrine Natacha Isaac

Vibrio cholerae is a pathogen that causes disease in millions of people every year by colonizing the small intestine and then secreting the potent cholera toxin. How the pathogen overcomes the colonization barrier created by the host’s natural microbiota i ...

2023

Difference in astringency of the main pea protein fractions

Francesco Stellacci, Hanna Fanny Clarisse Lesme

Interactions between food and saliva govern complex mouthfeel perceptions such as astringency. Herein, we present a study of the interactions of salivary proteins with the main pea protein fractions that are obtained by isoelectric and salt precipitation ( ...

Elsevier Sci Ltd2023

HD 213258: A new rapidly oscillating, super slowly rotating, strongly magnetic Ap star in a spectroscopic binary

Pierre North

We report on HD 213258, an Ap star that we recently identified as presenting a unique combination of rare, remarkable properties. Our study of this star is based on ESPaDOnS Stokes I and V data obtained at seven epochs spanning a time interval slightly sho ...

EDP SCIENCES S A2023

Resolving Galactic-scale Obscuration of X-Ray AGNs at z & GSIM; 1 with COSMOS-Web

Michaela Hirschmann

A large fraction of the accreting supermassive black hole population is shrouded by copious amounts of gas and dust, particularly in the distant (z & GSIM; 1) universe. While much of the obscuration is attributed to a parsec-scale torus, there is a known c ...

IOP Publishing Ltd2023

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Stephen William Wasilewski

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

EPFL2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Annotation-efficient image anomaly detection

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

The present invention proposes a method for detecting anomalous or out-of-distribution images in a machine learning system (1) comprising a pre-training network with a first encoder, and an anomaly detection network with a second encoder. The system is fir ...

2022

Importance of 3D radiative transfer effects on high-resolution NO2 remote sensing in cities

Marc Damien Schwärzel

Urban air quality is a major concern in the context of human health since cities are at the same time emission hot spots and home to a large fraction of the world's population. Airborne imaging spectrometers may be a valuable addition to traditional air po ...

EPFL2022

Medipix4, a high granularity four sides buttable pixel readout chip for high resolution spectroscopic X-ray imaging at rates compatible with medical CT scans

Viros Sriskaran

Medipix4 is the latest member in the Medipix/Timepix family of pixel detector chips aimed at high rate spectroscopic X-ray imaging using high-Z materials. The chip address the limitations of conventional hybrid pixel detectors for X-ray imaging. Its predec ...

EPFL2022

Host genomics of SARS-CoV-2 infection

Jacques Fellay, Christian Axel Wandall Thorball

SARS-CoV-2 infected a large fraction of humans in the past 2 years. The clinical presentation of acute infection varies greatly between individuals, ranging from asymptomatic or mild to life-threatening COVID-19 pneumonia with multi-organ complications. De ...

SPRINGERNATURE2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0

Michael Lehning, Océane Hames, Marc Schneebeli Zeugin, David Nicholas Wagner, Mahdi Jafari

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the depos ...

COPERNICUS GESELLSCHAFT MBH2022

How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications

Petr Motlicek, Juan Pablo Zuluaga Gomez, Amrutha Prasad

Recent work on self-supervised pre-training focus on leveraging large-scale unlabeled speech data to build robust end-to-end (E2E) acoustic models (AM) that can be later fine-tuned on downstream tasks e.g., automatic speech recognition (ASR). Yet, few work ...

IEEE2022