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Probabilistic small data global Well-Posedness of the energy-critical Maxwell-Klein-Gordon equation

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Statistical comparison of the performance of data-based models for sewer condition modeling

José Pedro Gamito de Saldanha Calado Matos

The present article proposes a methodology to consider the uncertainty intrinsic to data-based models when comparing their performance. The goal is to provide a quantification of the variability of this type of models due to the random nature of the calibr ...

2019

Learning new physics from a machine

Andrea Wulzer, Raffaele Tito D'Agnolo

We propose using neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The virtues of neural networks as unbiased function approximants make them particu ...

American Physical Society2019

Reducing Metadata Leakage from Encrypted Files and Communication with PURBs

Jean-Pierre Hubaux, Ludovic Barman, Kirill Nikitin, Matthew Joshua Underwood, Bryan Alexander Ford, Wouter Lueks

Most encrypted data formats leak metadata via their plaintext headers, such as format version, encryption schemes used, number of recipients who can decrypt the data, and even the recipients’ identities. This leakage can pose security and privacy risks to ...

Sciendo2019

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis

Kathryn Hess Bellwald, Cathrin Brisken, Jacques Rougemont, Rachel Marcone

Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...

2019

Amplitude Analysis of B-+/- -> pi(K+K-)-K-+/- Decays

Christoph Frei, Peter Clarke, Aurelio Bay, Minh Tâm Tran, Marc-Olivier Bettler, François Fleuret, Tatsuya Nakada, Guido Haefeli, Niko Neufeld, Olivier Schneider, Hans Dijkstra, Frédéric Teubert, Gerhard Raven, Mingkui Wang, Chitsanu Khurewathanakul, Frédéric Blanc, Matthew Needham, Axel Kuonen, Olivier Göran Girard, Liang Sun, Maxime Schubiger, Brice Emile Maurin, Thibaud Humair, Hang Yin, Xiaoxue Han, Greig Alan Cowan, Paolo Durante, Jessica Prisciandaro, Guillaume Max Pietrzyk, Matthieu Philippe Luther Marinangeli, Vladislav Balagura, Lino Ferreira Lopes, Zhirui Xu, Mark Tobin, Victor Coco, Violaine Bellée, Mirco Dorigo, Yu Zheng, Vincenzo Battista, Maurizio Martinelli, Tommaso Colombo, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms

Mikhail Kapralov, Amir Zandieh

Reconstructing continuous signals based on a small number of discrete samples is a fundamental problem across science and engineering. We are often interested in signals with "simple" Fourier structure - e.g., those involving frequencies within a bounded r ...

ASSOC COMPUTING MACHINERY2019

Deep Learning of Human Perception in Audio Event Classification

Samuel Denys Beuret, Yi Yu

In this paper, we introduce our recent studies on human perception in audio event classification. In particular, the pre-trained model VGGish is used as feature extractor to process audio data, and DenseNet is trained by and used as feature extractor for o ...

IEEE2018

Development of topological tools for the analysis of biological data

Rachel Marcone

There is a growing need for unbiased clustering algorithms, ideally automated to analyze complex data sets. Topological data analysis (TDA) has been used to approach this problem. This recent field of mathematics discerns characteristic features of a space ...

EPFL2018

The Mondrian Data Engine

Babak Falsafi, Javier Picorel Obando, Boris Robert Grot, Alexandros Daglis, Nooshin Sadat Mirzadeh, Dmitrii Ustiugov, Mario Paulo Drumond Lages De Oliveira, Dionysios Pnevmatikatos

The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, adva ...

2017

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Guido Andreassi

Maxim Borisyak

Dipanwita Dutta

Plamen Hristov Hopchev

Maria Elena Stramaglia

Ana Bárbara Rodrigues Cavalcante

Federico Leo Redi

Michel De Cian

Sebastian Schulte

Veronica Sølund Kirsebom

Aravindhan Venkateswaran

Luis Miguel Garcia Martin

Giovanni Carboni

Zheng Wang

The first amplitude analysis of the B-+/- -> pi(K+K-)-K-+/- decay is reported based on a data sample corresponding to an integrated luminosity of 3.0 fb(-1) of pp collisions recorded in 2011 and 2012 with the LHCb detector. The data are found to be best de ...

2019