Publications associées à Nettoyage de données

Rock You like a Hurricane: Taming Skew in Large Scale Analytics

Willy Zwaenepoel, Nicolas Schiper, Laurent Bindschaedler, Jasmina Malicevic, Ashvin Goel

Current cluster computing frameworks suffer from load imbalance and limited parallelism due to skewed data distributions, processing times, and machine speeds. We observe that the underlying cause for these issues in current systems is that they partition ...

2018

Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

José del Rocio Millán Ruiz, Jocelyne Bloch, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Inaki Asier Iturrate Gil, Aleksander Sobolewski, Stéphanie Martin

Excessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinson’s Disease (PD) motor symptoms. However, previous works have been inconsistent regarding the functional role of beta activity in untreated Parkinsonian states, quest ...

2018

Predicting Group Performance in Task-Based Interaction

Catharine Regina Monika Maria Oertel Genannt Bierbach

We address the problem of automatically predicting group performance on a task, using multimodal features derived from the group conversation. These include acoustic features extracted from the speech signal, and linguistic features derived from the conver ...

ASSOC COMPUTING MACHINERY2018

Deep Neural Networks for Multiple Speaker Detection and Localization

Jean-Marc Odobez, Petr Motlicek, Weipeng He

We propose to use neural networks for simultaneous detection and localization of multiple sound sources in human-robot interaction. In contrast to conventional signal processing techniques, neural network-based sound source localization methods require few ...

2018

CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning

Anastasia Ailamaki, Benjamin Cyrille Damien Gaidioz, Manolis Karpathiotakis, Styliani Asimina Giannakopoulou

Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. At the same time, the existing tools that att ...

Assoc Computing Machinery2017

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

Athanasios Nenes, Julia Schmale, Ghislain Gilles Jean-Michel Motos

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraS ...

2017

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia, Carlos Castillo

Applying classical time-series analysis techniques to online content is challenging, as web data tends to have data quality issues and is often incomplete, noisy, or poorly aligned. In this paper, we tackle the problem of predicting the evolution of a time ...

SPA: Sparse Photorealistic Animation Using a Single RGB-D Camera

Ronan Boulic, Eray Molla, Jingyu Yang, Kun Li

Photorealistic animation is a desirable technique for computer games and movie production. We propose a new method to synthesize plausible videos of human actors with new motions using a single cheap RGB-D camera. A small database is captured in a usual of ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Development of Bidirectional Cyclic Lateral Loading Protocols for Experimental Testing of Steel Wide-Flange Columns

Dimitrios Lignos, Ahmed Mohamed Ahmed Elkady

Steel columns in frame buildings subjected to earthquake shaking undergo bidirectional lateral drift demands. Till now, the majority of past experimental and numerical studies were primarily concerned with the unidirectional column behavior. This paper pro ...

2017

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Nettoyage de données

Rock You like a Hurricane: Taming Skew in Large Scale Analytics

Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

Predicting Group Performance in Task-Based Interaction

Deep Neural Networks for Multiple Speaker Detection and Localization

CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Fast iterative retrieval algorithm for ultrashort pulse characterization using dispersion scans

SPA: Sparse Photorealistic Animation Using a Single RGB-D Camera

Development of Bidirectional Cyclic Lateral Loading Protocols for Experimental Testing of Steel Wide-Flange Columns

Graph Chatbot

Chattez avec Graph Search

Rock You like a Hurricane: Taming Skew in Large Scale Analytics

Fast iterative retrieval algorithm for ultrashort pulse characterization using dispersion scans

CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning

SPA: Sparse Photorealistic Animation Using a Single RGB-D Camera

Deep Neural Networks for Multiple Speaker Detection and Localization

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Development of Bidirectional Cyclic Lateral Loading Protocols for Experimental Testing of Steel Wide-Flange Columns

Predicting Group Performance in Task-Based Interaction

Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition