From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: X-Original-To: caml-list@sympa.inria.fr Delivered-To: caml-list@sympa.inria.fr Received: from mail2-relais-roc.national.inria.fr (mail2-relais-roc.national.inria.fr [192.134.164.83]) by sympa.inria.fr (Postfix) with ESMTPS id 03ED07F058 for ; Mon, 28 Dec 2015 09:02:35 +0100 (CET) IronPort-PHdr: 9a23:daYjKxwTLtfTcArXCy+O+j09IxM/srCxBDY+r6Qd0eMUIJqq85mqBkHD//Il1AaPBtWFra8ZwLCJ7+jJYi8p39WoiDg6aptCVhsI2409vjcLJ4q7M3D9N+PgdCcgHc5PBxdP9nC/NlVJSo6lPwWB6kO74TNaIBjjLw09fr2zQd6MyZnqnLrtp9X6WEZhunmUWftKNhK4rAHc5IE9oLBJDeIP8CbPuWZCYO9MxGlldhq5lhf44dqsrtY4q3wD87AE3u9kcIPVN+RhEv0LRAkgKH0/sc33qQGRCkyA/HIZV2wMiVxHGQzA51fxWZK2uCr1uuNhgnHDY4qlcbdhRDKu7rxgTBjzhStCLTMy8XnWh8psl/AI8zy7oBkq7LTwRardYPVkeqbWVdwAQW9KGM1WUnoSUcuHc4ITAr9YZLUQlIL6vVZb9ESz Authentication-Results: mail2-smtp-roc.national.inria.fr; spf=None smtp.pra=grlmc@grlmc.com; spf=Pass smtp.mailfrom=grlmc@grlmc.com; spf=None smtp.helo=postmaster@smtp.ozongo.com Received-SPF: None (mail2-smtp-roc.national.inria.fr: no sender authenticity information available from domain of grlmc@grlmc.com) identity=pra; client-ip=95.128.157.207; receiver=mail2-smtp-roc.national.inria.fr; envelope-from="grlmc@grlmc.com"; x-sender="grlmc@grlmc.com"; x-conformance=sidf_compatible Received-SPF: Pass (mail2-smtp-roc.national.inria.fr: domain of grlmc@grlmc.com designates 95.128.157.207 as permitted sender) identity=mailfrom; client-ip=95.128.157.207; receiver=mail2-smtp-roc.national.inria.fr; envelope-from="grlmc@grlmc.com"; x-sender="grlmc@grlmc.com"; x-conformance=sidf_compatible; x-record-type="v=spf1" Received-SPF: None (mail2-smtp-roc.national.inria.fr: no sender authenticity information available from domain of postmaster@smtp.ozongo.com) identity=helo; client-ip=95.128.157.207; receiver=mail2-smtp-roc.national.inria.fr; envelope-from="grlmc@grlmc.com"; x-sender="postmaster@smtp.ozongo.com"; x-conformance=sidf_compatible X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: A0BtBADT64BWf8+dgF8bAyYahAxthGCDealuiX4GgmEYAQmCPYM+gQY8EAEBAQEBAQEBEAEBCwsKCCEtAYIqBIF+MisfAR9JAiENBTIBFBQBBIVRgkEKO4oAjXuPcIMWjn+GVYkwEH2BfAwuEAOBNwWSdIQGAQsTgV2DUIgKB2B8SoN8gneBKoQ4hECCBod1OYIBAR6CFz00AYMlAR+BKwEBAQ X-IPAS-Result: A0BtBADT64BWf8+dgF8bAyYahAxthGCDealuiX4GgmEYAQmCPYM+gQY8EAEBAQEBAQEBEAEBCwsKCCEtAYIqBIF+MisfAR9JAiENBTIBFBQBBIVRgkEKO4oAjXuPcIMWjn+GVYkwEH2BfAwuEAOBNwWSdIQGAQsTgV2DUIgKB2B8SoN8gneBKoQ4hECCBod1OYIBAR6CFz00AYMlAR+BKwEBAQ X-IronPort-AV: E=Sophos;i="5.20,489,1444687200"; d="scan'208,217";a="194751027" X-BulkT-Status: Yes Received: from smtp.ozongo.com ([95.128.157.207]) by mail2-smtp-roc.national.inria.fr with ESMTP; 28 Dec 2015 09:02:34 +0100 Received: by smtp.ozongo.com (Postfix, from userid 65534) id 928243EA57; Mon, 28 Dec 2015 09:02:34 +0100 (CET) Received: from webmail.ozongo.com (unknown [10.2.155.191]) (Authenticated sender: grlmc@grlmc.com) by smtp.ozongo.com (Postfix) with ESMTPA id 33FDB3E9B6; Mon, 28 Dec 2015 09:01:40 +0100 (CET) MIME-Version: 1.0 Content-Type: multipart/alternative; boundary="=_282687be24993ebdfb1cd04f4fb1b6d8" Date: Mon, 28 Dec 2015 09:01:39 +0100 From: GRLMC To: undisclosed-recipients:; Message-ID: X-Sender: grlmc@grlmc.com User-Agent: Roundcube Webmail/0.8.2 X-Validation-by: grlmc@grlmc.com Subject: [Caml-list] BigDat 2016: early registration deadline 8 January --=_282687be24993ebdfb1cd04f4fb1b6d8 Content-Transfer-Encoding: 8bit Content-Type: text/plain; charset=UTF-8 *To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line* ********************************************************   2ND INTERNATIONAL WINTER SCHOOLON BIG DATA   BIGDAT 2016 BILBAO, SPAIN FEBRUARY 8-12, 2016 Organized by: DeustoTech, University of Deusto Rovira i VirgiliUniversity http://grammars.grlmc.com/bigdat2016/ ******************************************************** --- Early registration deadline: January 8, 2016 --- ******************************************************** AIM: BigDat 2016 will be a research training event addressed to graduates and postgraduates in the first steps of their academic career. With a global scope, it aims at updating them about the most recent advances in the critical and fast developing area of big data, which covers a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, medicine, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience. Most big data subareas will be displayed, namely: foundations, infrastructure, management, search and mining, security and privacy, and applications. Main challenges of analytics, management and storage of big data will be identified through 4 keynote lectures, 19 six-hour courses, and 1 round table, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event. An open session will give participants the opportunity to present their own work in progress in 5 minutes. ADDRESSED TO: Graduates and postgraduates from around the world. There are no formal pre-requisites in terms of academic degrees. However, since there will be differences in the course levels, specific knowledge background may be assumed for some of them. BigDat 2016 is also appropriate for more senior people who want to keep themselves updated on recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators. REGIME: In addition to keynotes, 2-3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they will be willing to attend as well as to move from one to another. VENUE: BigDat 2016 will take place in Bilbao, the capital of the Basque Country region, famous for its gastronomy and the seat of the GuggenheimMuseum. The venue will be: DeustoTech, School of Engineering University of Deusto Avda. Universidades, 24 48014 Bilbao KEYNOTE SPEAKERS: Nektarios Benekos (European Organization for Nuclear Research), Role of Computing and Software in Particle Physics Chih-Jen Lin (NationalTaiwanUniversity), When and When Not to Use Distributed Machine Learning Jeffrey Ullman (StanfordUniversity), Theory of MapReduce Algorithms Alexandre Vaniachine (Argonne National Laboratory), Big Data Technologies and Data Science Methods in the Higgs Boson Discovery PROFESSORS AND COURSES: Nektarios Benekos (European Organization for Nuclear Research), [introductory/intermediate] Exploring the Mysteries of our Cosmos: the Big Deal between Big Data and Big Science Hendrik Blockeel (KU Leuven), [intermediate] Decision Trees for Big Data Analytics Edward Y. Chang (HTC Health, Taipei), [introductory/intermediate] Big Data Analytics for Healthcare: Scalable Algorithms and Applications Nello Cristianini (University of Bristol), [introductory] THINKBIG: Towards Large Scale Computational Social Sciences, History and Digital Humanities Ernesto Damiani (University of Milan & EBTIC/Khalifa University), [introductory/intermediate] Architectures, Models and Tools for Big-Data-as-a-Service Francisco Herrera (University of Granada), [introductory] Big Data Preprocessing George Karypis (University of Minnesota), [intermediate/advanced] Scaling Up Recommender Systems Chih-Jen Lin (NationalTaiwanUniversity), [introductory/intermediate] Large-scale Linear Classification Geoff McLachlan (University of Queensland), [intermediate/advanced] Big Data Extensions of Some Methods of Classification and Clustering Wladek Minor (University of Virginia), [introductory/intermediate] Big Data in Biomedical Sciences Raymond Ng (University of British Columbia), [introductory/intermediate] Mining and Summarizing Text Conversations Sankar K. Pal (Indian Statistical Institute), [introductory/advanced] Machine Intelligence and Granular Mining: Relevance to Big Data Erhard Rahm (University of Leipzig), [introductory/intermediate] Scalable and Privacy-preserving Data Integration Hanan Samet (University of Maryland), [introductory/intermediate] Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial Databases, Geographic Information Systems (GIS), and Location-based Services Jaideep Srivastava (Qatar Computing Research Institute), [intermediate] Social Computing: Computing as an Integral Tool to Understanding Human Behavior and Solving Problems of Social Relevance Jeffrey Ullman (StanfordUniversity), [introductory] Big Data Algorithms that Aren't Machine Learning Alexandre Vaniachine (Argonne National Laboratory), [introductory/advanced] Big Data: Comparison with Computational Models Xiaowei Xu (University of Arkansas, Little Rock), [introductory/advanced] Big Data Analytics for Social Networks Mohammed J. Zaki (Rensselaer Polytechnic Institute), [introductory/intermediate] Large Scale Graph Analytics and Mining OPEN SESSION An open session will collect 5-minute presentations of work in progress by participants. They should submit a half-page abstract containing title, authors, and summary of the research to adrian.dediu (at) urv.cat by February 5, 2016. ORGANIZING COMMITTEE: Adrian Horia Dediu Carlos Martín-Vide (co-chair) Iker Pastor López (co-chair) Borja Sanz (co-chair) Florentina Lilica Voicu REGISTRATION: It has to be done at http://grammars.grlmc.com/bigdat2016/registration.php The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an approximation of the respective demand for each course. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration facility disabled when the capacity of the venue will be complete. It is much recommended to register prior to the event. FEES: Participants are expected to attend full-time. Fees are a flat rate allowing the attendance to all courses during the week. There are several early registration deadlines. Fees depend on the registration deadline. ACCOMMODATION: Suggestions of accommodation are available on the webpage. CERTIFICATE: Participants will be delivered a certificate of attendance. QUESTIONS AND FURTHER INFORMATION: florentinalilica.voicu (at) urv.cat ACKNOWLEDGEMENTS: University of Deusto Rovira i Virgili University --=_282687be24993ebdfb1cd04f4fb1b6d8 Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset=UTF-8

*To be removed from our mailing list, please respond to= this message with UNSUBSCRIBE in the subject line*

 

*******************************************************= *

 

2nd INTERNATIONAL W= INTER SCHOOLON BIG DATA

 

BigDat 2016

 

Bilbao, Spain=

 

February 8-12, 2016

 

Organized by:

DeustoTech, University of Deusto

Rovira i VirgiliUniversity

 

http://grammars.grlmc.com/bigdat2016/

 

*******************************************************= *

 

--- Early r= egistration deadline: January 8, 2016 ---

 

*******************************************************= *

 

AIM:

 

BigDat 2016 will be a research training event addressed to graduates and= postgraduates in the first steps of their academic career. With a global s= cope, it aims at updating them about the most recent advances in the critic= al and fast developing area of big data, which covers a large spectrum of c= urrent exciting research and industrial innovation with an extraordinary po= tential for a huge impact on scientific discoveries, medicine, engineering,= business models, and society itself. Renowned academics and industry pione= ers will lecture and share their views with the audience.

 

Most big data subareas will be displayed, namely: foundations, infrastru= cture, management, search and mining, security and privacy, and application= s. Main challenges of analytics, management and storage of big data will be= identified through 4 keynote lectures, 19 six-hour courses, and 1 round ta= ble, which will tackle the most active and promising topics. The organizers= are convinced that outstanding speakers will attract the brightest and mos= t motivated students. Interaction will be a main component of the event. An= open session will give participants the opportunity to present their own w= ork in progress in 5 minutes.

 

ADDRESSED TO:

 

Graduates and postgraduates from around the world. There are no formal p= re-requisites in terms of academic degrees. However, since there will be di= fferences in the course levels, specific knowledge background may be assume= d for some of them. BigDat 2016 is also appropriate for more senior people = who want to keep themselves updated on recent developments and future trend= s. All will surely find it fruitful to listen and discuss with major resear= chers, industry leaders and innovators.

 

REGIME:

 

In addition to keynotes, 2-3 courses will run in parallel during the who= le event. Participants will be able to freely choose the courses they will = be willing to attend as well as to move from one to another.

 

VENUE:

 

BigDat 2016 will take place in Bilbao, the capital of the Basque Country= region, famous for its gastronomy and the seat of the GuggenheimMuseum. Th= e venue will be:

 

DeustoTech, School of Engineering

University of Deusto

Avda. Universidades, 24

48014 Bilbao

 

KEYNOTE SPEAKERS:

 

Nektarios Benekos (European Organization for Nuclear Research), Role of = Computing and Software in Particle Physics

 

Chih-Jen Lin (NationalTaiwanUniversity), When and When Not to Use Distri= buted Machine Learning

 

Jeffrey Ullman (StanfordUniversity), Theory of MapReduce Algorithms

 

Alexandre Vaniachine (Argonne National Laboratory), Big Data Technologie= s and Data Science Methods in the Higgs Boson Discovery

 

PROFESSORS AND COURSES:

 

Nektarios Benekos (European Organization for Nuclear Research), [introdu= ctory/intermediate] Exploring the Mysteries of our Cosmos: the Big Deal bet= ween Big Data and Big Science

 

Hendrik Blockeel (KU Leuven), [intermediate] Decision Trees for Big Data= Analytics

 

Edward Y. Chang (HTC Health, Taipei), [introductory/intermediate] Big Da= ta Analytics for Healthcare: Scalable Algorithms and Applications

 

Nello Cristianini (University of Bristol), [introductory] THINKBIG: Towa= rds Large Scale Computational Social Sciences, History and Digital Humaniti= es

 

Ernesto Damiani (University of Milan & EBTIC/Khalifa University), [i= ntroductory/intermediate] Architectures, Models and Tools for Big-Data-as-a= -Service

 

Francisco Herrera (University of Granada), [introductory] Big Data Prepr= ocessing

 

George Karypis (University of Minnesota), [intermediate/advanced] Scalin= g Up Recommender Systems

 

Chih-Jen Lin (NationalTaiwanUniversity), [introductory/intermediate] Lar= ge-scale Linear Classification

 

Geoff McLachlan (University of Queensland), [intermediate/advanced] Big = Data Extensions of Some Methods of Classification and Clustering

 

Wladek Minor (University of Virginia), [introductory/intermediate] Big D= ata in Biomedical Sciences

 

Raymond Ng (University of British Columbia), [introductory/intermediate]= Mining and Summarizing Text Conversations

 

Sankar K. Pal (Indian Statistical Institute), [introductory/advanced] Ma= chine Intelligence and Granular Mining: Relevance to Big Data

 

Erhard Rahm (University of Leipzig), [introductory/intermediate] Scalabl= e and Privacy-preserving Data Integration

 

Hanan Samet (University of Maryland), [introductory/intermediate] Sortin= g in Space: Multidimensional, Spatial, and Metric Data Structures for Appli= cations in Spatial Databases, Geographic Information Systems (GIS), and Loc= ation-based Services

 

Jaideep Srivastava (Qatar Computing Research Institute), [intermediate] = Social Computing: Computing as an Integral Tool to Understanding Human Beha= vior and Solving Problems of Social Relevance

 

Jeffrey Ullman (StanfordUniversity), [introductory] Big Data Algorithms = that Aren't Machine Learning

 

Alexandre Vaniachine (Argonne National Laboratory), [introductory/advanc= ed] Big Data: Comparison with Computational Models

 

Xiaowei Xu (University of Arkansas, Little Rock), [introductory/advanced= ] Big Data Analytics for Social Networks

 

Mohammed J. Zaki (Rensselaer Polytechnic Institute), [introductory/inter= mediate] Large Scale Graph Analytics and Mining

 

OPEN SESSION

 

An open session will collect 5-minute presentations of work in progress = by participants. They should submit a half-page abstract containing title, = authors, and summary of the research to adrian.dediu (at) urv.cat by Februa= ry 5, 2016.

 

ORGANIZING COMMITTEE:

 

Adrian Horia Dediu

Carlos Martín-Vide (co-chair)

Iker Pastor López (co-chair)

Borja Sanz (co-chair)

Florentina Lilica Voicu

 

REGISTRATION:

 

It has to be done at

 

http://grammars.grlmc.com/bigdat2016/registration.php

 

The selection of up to 8 courses requested in the registration template = is only tentative and non-binding. For the sake of organization, it will be= helpful to have an approximation of the respective demand for each course.=

 

Since the capacity of the venue is limited, registration requests will b= e processed on a first come first served basis. The registration period wil= l be closed and the on-line registration facility disabled when the capacit= y of the venue will be complete. It is much recommended to register prior t= o the event.

 

FEES:

 

Participants are expected to attend full-time. Fees are a flat rate allo= wing the attendance to all courses during the week. There are several early= registration deadlines. Fees depend on the registration deadline.

 

ACCOMMODATION:

 

Suggestions of accommodation are available on the webpage.

 

CERTIFICATE:

 

Participants will be delivered a certificate of attendance.

 

QUESTIONS AND FURTHER INFORMATION:

 

florentinalilica.voicu (at) urv.cat

 

ACKNOWLEDGEMENTS:

 

University of Deusto

Rovira i Virgili University

 

 
--=_282687be24993ebdfb1cd04f4fb1b6d8--