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Related publications (31)

An Event-Based System for Low-Power ECG QRS Complex Detection

David Atienza Alonso, Tomas Teijeiro Campo, Silvio Zanoli, Fabio Montagna

One of the greatest challenges in the design of modern wearable devices is energy efficiency. While data processing and communication have received a lot of attention from the industry and academia, leading to highly efficient microcontrollers and transmis ...

IEEE2020

Variance-Reduced Stochastic Learning Under Random Reshuffling

Ali H. Sayed, Bicheng Ying, Kun Yuan

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizer. The existing convergence results assume uniform d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Assessment of the breakthrough of micropollutants in full-scale granular activated carbon adsorbers by rapid small-scale column tests and a novel pilot-scale sampling approach

Urs von Gunten, Juliane Hollender

This study aimed to compare three approaches for predicting the service life of full-scale GAC adsorbers for the removal of micropollutants. The approaches included (i) rapid small-scale column tests (RSSCTs), (ii) two pilot-scale sampling approaches, and ...

ROYAL SOC CHEMISTRY2020

CODEX clusters: Survey, catalog, and cosmology of the X-ray luminosity function

Jean-Paul Richard Kneib, Johan Comparat, Ghazaleh Erfanianfar

Context. Large area catalogs of galaxy clusters constructed from ROSAT All-Sky Survey provide the basis for our knowledge of the population of clusters thanks to long-term multiwavelength efforts to follow up observations of these clusters.Aims. The advent ...

EDP SCIENCES S A2020

A Learning-Based Framework for Quantized Compressed Sensing

Volkan Cevher, Rabeeh Karimi Mahabadi, Junhong Lin

Sparse recovery from undersampled random quan- tization measurements is a recent active research topic. Previous work asserts that stable recovery can be guaranteed via the basis pursuit dequantizer (BPDQ) if the measurements number is large enough, consid ...

IEEE Institute of Electrical and Electronics Engineers2019

Multithermal-Multibaric Molecular Simulations from a Variational Principle

Pablo Miguel Piaggi, Michele Parrinello

We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev. Lett. 113, 0906 ...

2019

Distributed sampling for rational approximation of the acoustic scattering of an airfoil

Francesca Bonizzoni, Davide Pradovera

In this paper we compute a reduced order model for a time‐harmonic external acoustic scattering problem with parametric frequency. The employed technique is minimal rational interpolation, an explicit moment‐matching method for Hilbert space‐valued meromor ...

2019

Interactive Optimization With Parallel Coordinates: Exploring Multidimensional Spaces for Decision Support

François Maréchal, Nils Christian Schüler, Sébastien Cajot

Interactive optimization methods are particularly suited for letting human decision makers learn about a problem, while a computer learns about their preferences to generate relevant solutions. For interactive optimization methods to be adopted in practice ...

2019

Search for CP violation through an amplitude analysis of D-0 K+K-+- decays

Olivier Schneider, Guido Haefeli, Yiming Li, Aurelio Bay, Frédéric Blanc, Tatsuya Nakada, Christoph Frei, Michel De Cian, Elena Graverini, Pietro Marino, Federico Leo Redi, Violaine Bellée, Luca Pescatore, François Fleuret, Pavol Stefko, Tara Nanut, Chitsanu Khurewathanakul, Maria Elena Stramaglia, Vladimir Macko, Renato Quagliani, Federico Betti, Aravindhan Venkateswaran, Luis Miguel Garcia Martin, Vitalii Lisovskyi, Jian Wang, Mingkui Wang, Zhirui Xu, Yi Zhang, Lei Zhang, Jessica Prisciandaro, Mark Tobin, Minh Tâm Tran, Niko Neufeld, Matthew Needham, Marc-Olivier Bettler, Greig Alan Cowan, Maurizio Martinelli, Vladislav Balagura, Donal Patrick Hill, Liang Sun, Mirco Dorigo, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Reactor simulations with nuclear data uncertainties

Andreas Pautz, Winfried Zwermann, Friederike Bostelmann, Alexander Aures

The paper demonstrates the influence of uncertainties in microscopic nuclear data on the results of reactor simulations, both for stationary and transient states. It gives an overview on the methods in use for uncertainty and sensitivity analyses with resp ...

ELSEVIER SCIENCE SA2019

Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network

Jean-Philippe Thiran

Training robust deep learning (DL) systems for medical image classification or segmentation is challenging due to limited images covering different disease types and severity. We propose an active learning (AL) framework to select most informative samples ...

Springer2018

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Jean Wicht

Xiaoxue Han

Liupan An

Plamen Hristov Hopchev

Guillaume Max Pietrzyk

A search for CP violation in the Cabibbo-suppressed D-0 K+K-+- decay mode is performed using an amplitude analysis. The measurement uses a sample of pp collisions recorded by the LHCb experiment during 2011 and 2012, corresponding to an integrated luminosi ...

Springer Nature2019