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Conférence

Le Paris Summit on Big data aura lieu mardi 9 mai 2017 à Télécom ParisTech

Yanlei Diao, membre de l'équipe CEDAR, fait partie du comité d'organisation de la seconde édition du Paris Summit on Big Data qui aura lieu le mardi 9 mai 2017 de 8h à 18h à Télécom ParisTech, à Paris.

  • Date : 9/05/2017

There has been significant interest in big data techniques and applications in recent years. The goal of this all-day summit is to bring together researchers from the greater Paris area with an interest in big data and data science, together with industry experts, to discuss our collective research strengths and look for opportunities for future collaborations.

This summit will showcase a number of research projects of high relevance and impact, and present a plenary student poster session to broadly cover projects on big data in the local area.

We welcome participation of all researchers, students, industry experts, and practitioners with an interest in big data and data science, as well as applications of big data in various domains.

Registration for the summit is free but compulsory! (before May 2)

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PROGRAM

08:00 Registration  
08:30 Introduction to the event  
08:45 Keynote: Probabilistic Numerics — Uncertainty in Computation – Philipp Hennig (Max Planck Institute for Intelligent Systems)  
10:00 Coffee break  
10:30 Technical talks 1  
Content management techniques and tools for fact-checking – François Goasdoué, Ioana Manolescu and Xavier Tannier  
Blocking for Big Data Integration – George Papadakis and Themis Palpanas  
Schema Inference for Massive JSON Datasets – Mohamed-Amine Baazizi, Ben Lahmar Houssem, Dario Colazzo, Giorgio Ghelli and Carlo Sartiani  
Kernel Square-Loss Exemplar Machines for Image Retrieval – Rafael Sampaio de Rezende, Joaquin Zepeda, Jean Ponce, Francis Bach and Patrick Pérez  
Online Model-Free Influence Maximization with Persistence – Paul Lagrée, Olivier Cappé, Bogdan Cautis and Silviu Maniu  
12:10 Lunch break  
13:30 Technical talks 2  
Structuring deep networks – Édouard Oyallon  
On the benefits of output sparsity for multi-label classification – Evgenii Chzhen, Christophe Denis, Mohamed Hebiri and Joseph Salmon  
scikit-learn: open, easy, yet versatile machine learning – Gael Varoquaux  
14:30 Keynote: Social Machines and Social Data – Peter Buneman (University of Edinburgh)  
15:45 Poster session & coffee break  
A deep learning based approach for performance optimization in big data systems – Fei Song, Zhao Cao and Yanlei Diao  
Dealing with incompletness in Knowledge Bases, a class-based approach – Jonathan Lajus  
EVIDENSE : Allowing a Large-Scale Analysis of the Coverage of Crisis Events in Social Media – Oana Denisa Balalau and Mauro Sozio  
Extracting Linked Data from statistic spreadsheets – Tien-Duc Cao, Ioana Manolescu and Xavier Tannier  
Indexing and Mining Very Large Collections of Data Series with Varying Lengths – Michele Linardi and Themis Palpanas  
Iterative and Expressive Queries for Big Data Series – Anna Gogolou, Anastasia Bezerianos, Theophanis Tsandilas and Themis Palpanas  
Large Scale Density-friendly Graph Decomposition via Convex Programming – Maximilien Danisch, Hubert Chan and Mauro Sozio  
Metagame analysis for team-based competitive games – Sylvain Lefebvre and Denis Maurel  
Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling – Christophe Dupuy and Francis Bach  
ParADS: Scalable Indexing of Very Large Data Series Collections Using Modern Hardware – Botao Peng and Themis Palpanas  
Random Fourier Features For Operator-Valued Kernels – Romain Brault, Markus Heinonen and Florence d'Alché-buc  
Side-Information Regularized Matrix Factorization – Paul-Henri Perrin, Florian Yger, Dario Colazzo and Jamal Atif  
Thymeflow: a personal knowledge base system – David Montoya  
Uncertainty Sampling and Optimization for Interactive Database Exploration – Liping Peng, Enhui Huang, Yuqing Xing, Anna Liu and Yanlei Diao  
World wealth & income database – Konstantinos Skianis and Michalis Vazirgiannis  
16:45 Technical talks 3  
A Circuit-Based Approach to Efficient Enumeration – Antoine Amarilli, Pierre Bourhis, Louis Jachiet and Stefan Mengel  
Inventory prediction in foreign exchange markets – Damien Challet, Rémy Chicheportiche, Mehdi Lallouache and Serge Kassibrakis  
Model Aggregation for Production Forecasting of Oil and Gas – Sebastien Da Veiga, Raphael Deswarte, Veronique Gervais-Couplet and Gilles Stoltz  
17:45 Closing cocktail

En savoir +

Mots-clés : Inria Saclay – Île-de-France Big data Yanlei DIAO Cedar

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