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Publications associées (161)

Fingerprinting Big Data: The Case of KNN Graph Construction

Rachid Guerraoui, Anne-Marie Kermarrec, Olivier Ruas

We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...

2019

Stochastic Learning Under Random Reshuffling With Constant Step-Sizes

Ali H. Sayed, Stefan Vlaski, Bicheng Ying, Kun Yuan

In empirical risk optimization, it has been observed that stochastic gradient implementations that rely on random reshuffling of the data achieve better performance than implementations that rely on sampling the data uniformly. Recent works have pursued ju ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Model-Independent Observation of Exotic Contributions to B degrees -> J/psi K+pi(-) Decays

Jian Wang, Olivier Schneider, Yiming Li, Yi Zhang, Aurelio Bay, Guido Haefeli, Christoph Frei, Frédéric Blanc, Tatsuya Nakada, Michel De Cian, Luca Pescatore, François Fleuret, Elena Graverini, Chitsanu Khurewathanakul, Renato Quagliani, Maria Vieites Diaz, Federico Betti, Aravindhan Venkateswaran, Vitalii Lisovskyi, Katharina Müller, Sebastian Schulte, Veronica Sølund Kirsebom, Mingkui Wang, Zhirui Xu, 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, Pietro Marino, Mirco Dorigo, Xiaoxue Han, Liupan An, Federico Leo Redi, Plamen Hristov Hopchev, Thibaud Humair, Maxime Schubiger, Hang Yin, Guido Andreassi, Violaine Bellée, Olivier Göran Girard, Axel Kuonen, Preema Rennee Pais, Pavol Stefko, Tara Nanut, Maria Elena Stramaglia, Tommaso Colombo, Vladimir Macko, Guillaume Max Pietrzyk, Evgenii Shmanin, Dipanwita Dutta, Zheng Wang, Yi Wang, Hans Dijkstra, Gerhard Raven, Peter Clarke, Frédéric Teubert, Giovanni Carboni, Victor Coco, Adam Davis, Paolo Durante, Wenyu Zhang, Yu Zheng, Anton Petrov, Maxim Borisyak, Feng Jiang, Zhipeng Tang, Luis Alberto Granado Cardoso, Daniel Hugo Cámpora Pérez, Alexander Vasiliev

An angular analysis of B degrees -> J/psi K+pi(-) decays is performed, using proton-proton collision data corresponding to an integrated luminosity of 3 fb(-1) collected with the LHCb detector. The m(K+pi(-) ) spectrum is divided into fine bins. In each m( ...

2019

Efficient Query Processing for Spatial and Temporal Data Exploration

Eleni Tzirita Zacharatou

Core to many scientific and analytics applications are spatial data capturing the position or shape of objects in space, and time series recording the values of a process over time. Effective analysis of such data requires a shift from confirmatory pipelin ...

EPFL2019

Designing for impact: a conceptual framework for learning analytics as self-assessment tools

Patrick Jermann, Roland John Tormey, Cécile Hardebolle, Francisco Pereira Correia Pinto

Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical m ...

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD2019

Quantiﬁcation of traﬃc and temperature eﬀects on the fatigue safety of a reinforced-concrete bridge deck based on monitoring data

Eugen Brühwiler, Imane Bayane, Amol Mankar

For assessment of existing reinforced-concrete bridges, only few rules and recommendations are available, and engineers meanwhile apply design codes for new bridges to evaluate the fatigue safety of existing bridges leading to non-realistic approaches and ...

2019

Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Jean-Philippe Thiran

Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem is especially acute, where there is a severe class imbalance. We propose an ...

2019

Exploring 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

What-if Analysis with Conflicting Goals: Recommending Data Ranges for Exploration

Thành Tâm Nguyên

IEEE2018

Architecture and Experimental Validation of a Low-Latency Phasor Data Concentrator

Mario Paolone, Asja Derviskadic, Paolo Romano, Marco Pignati

The paper presents the design principles of a Phasor Data Concentrator (PDC) that implements both the absolute and relative time data pushing logics together with a third one that aims at minimizing the latency introduced by the PDC without increasing the ...

2018

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