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Learning of robust spectral graph dictionaries for distributed processing

Publications associées (31)

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

IOP Publishing Ltd2023

Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics

Anastasia Ailamaki, Viktor Sanca

Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...

2023

Euclid preparation XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

Slobodan Ilic, Georges Meylan, Frédéric Courbin, Richard Massey, Maurizio Martinelli, Gianluca Castignani, Marcello Farina, Yi Wang

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morpholo ...

2023

A Multimodal Dataset for Automatic Edge-AI Cough Detection

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo, Jérôme Paul Rémy Thevenot

Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. Automatic cough counting tools must provide accurate information, while runnin ...

New York2023

Optimizing Data Processing for Nanodiamond Based Relaxometry

Mayeul Sylvain Chipaux

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

WILEY2023

Federated Linear Bandit Learning via Over-the-air Computation

Xin Liu, Ting Wang, Yuning Jiang

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model upd ...

IEEE2023

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Jürg Alexander Schiffmann, Cyril Picard, Soheyl Massoudi

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

ASME Amer Soc Mechanical Engineers2023

GTC Follow-up Observations of Very Metal-poor Star Candidates from DESI

Pascale Jablonka, Arjun Dey

The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of similar to 10, improving the sample statistics to study the early chemical evolution of the Mil ...

Iop Publishing Ltd2023

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Claudio Bruschini, Edoardo Charbon, Andrei Ardelean, Mohit Gupta

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Ieee Computer Soc2023

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Jean-Philippe Thiran, Roser Vinals Terres

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

2023

Spatially multiplexed single-molecule translocations through a nanopore at controlled speeds

Aleksandra Radenovic, Georg Fantner, Samuel Mendes Leitão, Barney Frederick Drake, Sanjin Marion, Vytautas Navikas, Simon Finn Mayer, Helena Miljkovic

In current nanopore-based label-free single-molecule sensing technologies, stochastic processes influence the selection of translocating molecule, translocation rate and translocation velocity. As a result, single-molecule translocations are challenging to ...

2023