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EARLINET: the European Aerosol Lidar Network
Publications associées (33)
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As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...
EPFL2024A 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 ...
2023incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment
A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...
2023Dynamism in the context of views out: A literature review
Marilyne Andersen, Caroline Karmann, Yunjoung Cho
Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...
2023Virtual metrology applied to milling process
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Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...
EPFL2022Budget-Bounded Incentives for Federated Learning
Boi Faltings, Aris Filos Ratsikas, Adam Julian Richardson
We consider federated learning settings with independent, self-interested participants. As all contributions are made privately, participants may be tempted to free-ride and provide redundant or low-quality data while still enjoying the benefits of the FL ...
Springer Nature Switzerland AG 20202022Privacy and Integrity Preserving Computations with CRISP
Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Sylvain Chatel, Apostolos Pyrgelis
In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users may want to prot ...
USENIX ASSOC2021On the adjustment, calibration and orientation of drone photogrammetry and laser-scanning
Emmanuel Pierre Quentin Clédat
Centimetre level precision mapping is essential for many applications such as land-use, infrastructure inspection, cultural heritage preservation, and construction site monitoring. However, the acquisition and its preparation (in particular the setting of ...
EPFL2020Product Quality Improvement Policies in Industry 4.0: Characteristics, Enabling Factors, Barriers, and Evolution Toward Zero Defect Manufacturing
Dimitrios Kyritsis, Gökan May, Foivos Psarommatis Giannakopoulos
In the competitive market of manufacturing, quality is a criterion of primary importance in order to win market share. Quality improvement must be coupled with performance point of view. Lean Manufacturing, Six Sigma, Lean Six Sigma, Total Quality Manageme ...
2020Exploring Data Partitions for What-if Analysis
Quoc Viet Hung Nguyen, Thành Tâm Nguyên
What-if analysis is a data-intensive exploration to inspect how changes in a set of input parameters of a model influence some outcomes. It is motivated by a user trying to understand the sensitivity of a model to a certain parameter in order to reach a se ...
2018