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Publications associées (28)

Scalable and Privacy-Preserving Federated Principal Component Analysis

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Joao André Gomes de Sá e Sousa, David Jules Froelicher, Jean-Philippe Léonard Bossuat

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

IEEE COMPUTER SOC2023

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Jürg Alexander Schiffmann, Cyril Picard

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

Amer Soc Mechanical Engineers2023

Sensing Eating Events in Context: A Smartphone-Only Approach

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

While the task of automatically detecting eating events has been examined in prior work using various wearable devices, the use of smartphones as standalone devices to infer eating events remains an open issue. This paper proposes a framework that infers e ...

2022

Pollution mask for the continuous corrected particle number concentration data in 1 min resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020

Julia Schmale, Andrea Baccarini, Ivo Fabio Beck, Hélène Paule Angot

This dataset contains a pollution flag in 1 min time resolution. It is derived by the pollution detection algorithm (PDA) based on the corrected particle number concentration data (DOI upcoming) measured during the year long MOSAiC expedition from October ...

Zenodo2022

Preprocessing Antarctic Weather Station (AWS) data in python

Michael Lehning, Franziska Gerber

There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of di ...

Zenodo2022

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Boi Faltings, Aleksei Triastcyn

We consider the problem of enhancing user privacy in common data analysis and machine learning development tasks, such as data annotation and inspection, by substituting the real data with samples from a generative adversarial network. We propose employing ...

MDPI2022

Probing gravity with the DES-CMASS sample and BOSS spectroscopy

Eduardo Sanchez, Jonathan Andrew Blazek

The DES-CMASS sample (DMASS) is designed to optimally combine the weak lensing measurements from the Dark Energy Survey (DES) and redshift-space distortions (RSD) probed by the CMASS galaxy sample from the Baryonic Oscillation Spectroscopic Survey. In this ...

2022

Towards reproducible software studies with MAO and Renku

Christine Choirat, Pamela Isabel Delgado Borda

In software engineering, the developers' joy of decomposing and recomposing microservice-based applications has led to an enormous wave of microservice artefact technologies. To understand them better, researchers perform hundreds of experiments and empiri ...

ELSEVIER2022