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Scalable and Privacy-Preserving Federated Principal Component Analysis

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

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Henry Markram, Sean Lewis Hill, Samuel Claude Kerrien, Carolina Johanna Elisabeth Lindqvist, Alejandra Garcia Rojas Martinez, Huanxiang Lu, Mohameth François Sy, Anna-Kristin Kaufmann, Jonathan Raël Lurie, Henry Genet

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

2023

Continuous corrected particle number concentration data in 10 sec resolution measured in the Swiss aerosol container using a whole air inlet during MOSAiC 2019/2020

Julia Schmale, Ivo Fabio Beck

This dataset contains corrected particle number concentration data measured during the year-long MOSAiC expedition from October 2019 to September 2020. Some periods of the measurements were affected by repeated step changes in the particle number concentra ...

Zenodo2023

Bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols measured in the Swiss container during MOSAiC 2019/2020

Julia Schmale, Benjamin Jérémy Laurent Heutte, Ivo Fabio Beck, Imad El Haddad, Hélène Paule Angot, Lubna Dada

This dataset contains the bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols (NR-PM1) measured during the MOSAiC expedition from October 2019 to July 2020. These include the mass concentrations of sulfate (S ...

Zenodo2023

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Mohammad Ali Shaeri

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

2023

Genetic features and genomic targets of human KRAB-zinc finger proteins

Didier Trono, Jacques Fellay, Priscilla Turelli, Christian Axel Wandall Thorball, Sandra Eloise Kjeldsen, Evaristo Jose Planet Letschert, Julien Léonard Duc, Cyril David Son-Tuyên Pulver, Romain Forey, Bara Khubieh

Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) are one of the largest groups of transcription factors encoded by tetrapods, with 378 members in human alone. KZFP genes are often grouped in clusters reflecting amplification by ...

2023

Shared metadata for data-centric materials science

Giovanni Pizzi, Ronald Earle Miller, Gian-Marco Rignanese, Carsten Baldauf, Matthias Scheffler, Tristan Bereau

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

Nature Portfolio2023

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Ljubomir Rokvic, Panayiotis Danassis

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

Center-aware Adversarial Augmentation for Single Domain Generalization

Mathieu Salzmann, Zhiye Wang

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

IEEE COMPUTER SOC2023

An Annotated Corpus of Tonal Piano Music from the Long 19th Century

Martin Alois Rohrmeier, Fabian Claude Moss, Johannes Hentschel, Markus Franz Josef Neuwirth

We present a dataset of 264 annotated piano pieces of nine composers, composed in the long 19th century (https://doi.org/10.5281/zenodo.7483349). Annotations adhere to the DCML harmony annotation standard and include Roman numerals, phrase boundaries, and ...

Ohio State Univ, Sch Music2023

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Scalable and Privacy-Preserving Federated Principal Component Analysis

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

IEEE COMPUTER SOC2023

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

2023

Continuous corrected particle number concentration data in 10 sec resolution measured in the Swiss aerosol container using a whole air inlet during MOSAiC 2019/2020

Julia Schmale, Ivo Fabio Beck

Zenodo2023

Bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols measured in the Swiss container during MOSAiC 2019/2020

Julia Schmale, Benjamin Jérémy Laurent Heutte, Ivo Fabio Beck, Imad El Haddad, Hélène Paule Angot, Lubna Dada

Zenodo2023