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

Linda Casals lindac at dimacs.rutgers.edu
Mon Feb 17 11:46:38 EST 2014


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DIMACS/CCICADA Workshop on Systems and Analytics of Big Data

  March 17 - 18, 2014
  DIMACS Center, CoRE Building, Rutgers University

Organizers:
    Joseph Gonzalez, UC Berkeley 
    Daniel Hsu, Columbia University 
    Li Erran Li, Bell Labs, erranlli at gmail.com 

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).

************************************************
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.  

***Call for Posters:***

We are soliciting poster abstracts for ongoing work in research and
applications at the intersection of Analytics, Machine Learning, and
Systems. 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. 
    
Poster abstracts should be one page (PDF) highlighting ongoing work
and preliminary results. Submissions should be sent to
biglearning at dimacs.rutgers.edu by March 3, 2014.

Accepted submissions will receive free registration and may also be
selected for spotlight presentations. 

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Workshop Program:

Monday, March 17, 2014

 8:45 -  9:00  Opening Remarks
               Welcome Message from the organizers: 
               Joseph Gonzalez, Daniel Hsu, and Li Erran Li

 9:00 - 10:00  Low-latency Distributed Analytics in Naiad
               Derek Murray, Microsoft Research Silicon Valley Lab 

10:00 - 11:00  Counterfactual Reasoning and Learning Systems
               Leon Bottou, Microsoft Research

11:00 - 11:30  Break

11:30 - 12:30  Large Scale Graph-Parallel Computation for Machine 
               Learning: Applications and Systems
               Joseph Gonzalez, Berkeley

12:30 -  1:20  Lunch Break

 1:20 -  1:30  Director's Welcome 
               Rebecca Wright, Director of DIMACS

 1:30 -  2:30  Beyond Jeopardy! Adapting Watson to 
               New Domains Using Distributional Semantics
               Alfio Gliozzo

 2:30 -  3:30  CloudCV: Computer Vision as a Cloud Service
               Dhruv Batra, Virginia Tech

 3:30 -  4:00  Break

 4:00 -  5:00  Panel on Systems and Analytics of Big Data
               Panelists:

 5:00 -  6:00  Posters

 6:00 -  8:00  Dinner

Tuesday, March 18, 2014

 9:00 - 10:00  MLbase: A User-Friendly System for Distributed 
               Machine Learning
               Ameet Talwalkar and Evan Sparks, Berkeley

10:00 - 11:00  Machine Learning
               Alex Smola, CMU

11:00 - 11:30  Break

 1:30 -  2:30  The Thorn in the Side of Big Data: Too Few Artists
               Christopher (Chris) Re, Stanford

12:30 -  1:30  Lunch and Workshop Adjourn

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Workshop web site (including registration):  

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



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