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[CCICADA-announce] DIMACS/CCICADA Workshop on Systems and Analytics of Big Data

Linda Casals lindac at dimacs.rutgers.edu
Fri Sep 13 12:36:20 EDT 2013


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DIMACS/CCICADA Workshop on Systems and Analytics of Big Data

    February 10 - 11, 2014** 
    DIMACS Center, CoRE Building, Rutgers University

  Organizers:
    Li Erran Li, Bell Labs, erranlli at gmail.com 
    Kathleen R. McKeown, Columbia University, kathy at cs.columbia.edu 

Presented under the auspices of the Special Focus on Information
Sharing and Dynamic Data Analysis and The Command, Control, and
Interoperability Center for Advanced Data Analysis (CCICADA).

**Note Date change
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Workshop Announcement:

Tremendous progress has been made in systems and analytics of big
data, e.g. Hadoop/MapReduce, STORM. However, modern data analytics
faces a confluence of growing challenges. First, the increasing data
deluge in social networks, online retails, web pages, mobile data, etc
creates the need to scale out across hundreds of thousands of
commodity machines. Second, the complexity of data analytics has also
grown to include sophisticated machine learning algorithm with data
dependencies. Third, many systems process streaming data and have real
time requirements.

We believe that this emerging field will benefit from close
interaction among researchers and industry practitioners. To this end,
we are planning to organize a DIMACS workshop where we bring together
academics and practitioners in computer systems, databases,
networking, machine learning, and algorithms to share their research
accomplishments and identify core problems on big data.

Topics of interest include but are not limited to the following:

    Systems Issues related to large datasets: storage, data
    centers/clouds, streaming system, and architecture.
    
    New programming model for big data beyond Hadoop/MapReduce, STORM,
    streaming languages
    
    Streaming big data processing
    
    Mining algorithms of big data in non-traditional formats
    (unstructured, semi-structured)
    
    Scalable, distributed and parallel algorithms
    
    Applications: mobile data, social network systems, smart grid, social
    media systems, scientific data mining, environmental, health
    analytics, financial analytics and smart cities.

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Call for Participation:

Talks are by invitation only.

Attendance at the workshop is open to all interested participants
(subject to space limitations). Please register if you would like to
attend this workshop.

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Workshop web site (including registration):  

 http://dimacs.rutgers.edu/Workshops/Analytics/

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