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Workshop on Living Analytics: Analyzing High-Dimensional Behavioral and Other Data from Dynamic Network Environments 1
(26 - 28 February 2014)

Jointly organized with Living Analytics Research Centre, SMU


Organizing Committee · Visitors and Participants · Overview · Activities · Venue



This program is co-sponsored with

Living Analytics Research Centre

Singapore Management University

Carnegie Mellon University

 Organizing Committee

 Visitors and Participants





"Big data" come in a variety of forms, but especially common are large high-dimensional electronic databases, e.g., involving transactions or genetic and related medical data, where the units of interest exist in a networked environment.  Analytical statistical methods and machine learning tools for analyzing such data involve finding low-dimensional representations and the direct exploitation of the network links to understand dependencies among units.   

The Living Analytics Research Centre (LARC), which is jointly operated by Carnegie Mellon University and Singapore Management University, has been especially focused on the development and use of such methods for analyzing data from commercial partners in Singapore.  Experimenting in such dynamic network environments is a special problem of interest to LARC and its researchers and commercial partners.

The aims of the proposed program is to facilitate such research by

  • Introducing current living analytics research activities to other mathematical science, machine learning, and statistical researchers in Singapore.
  • Broadening the statistical research underpinnings of models and computational algorithms for living analytics research and other research activities involving the analysis of large high-dimensional databases.
  • Foster interaction among scientists developing methodology for "big data" problems using living analytics as a focal point.
  • Chart new directions of research; and explore possible collaborations, especially among the different groups.



The two-day workshop will be hosted by LARC and IMS on the following days:



27 Feb 2014

Ngee Ann Kongsi Auditorium, School of Accountancy, SMU

28 Feb 2014

University Hall Auditorium, Lee Kong Chian Wing, Level 2
21 Lower Kent Ridge Road, S(119077), NUS

Invited Speakers


Thursday, 27 Feb 2014
Venue: Ngee Ann Kongsi Auditorium, School of Accountancy, SMU

09:00am - 10:00am

Welcome by Program Organizers
LARC-LiveLabs Overview (PDF)
Stephen Fienberg, Carnegie Mellon University, USA
Lim Ee-Peng, Singapore Management University

10:00am - 10:30am

--- Coffee Break ---

10:30am - 11:30am

Gaussian process emulation of models with massive output
Jim Berger, Duke University, USA

11:30am - 12:15pm

Statistical computing in protein folding
Samuel Kou, Harvard University, USA

12:15pm - 01:45pm

--- Lunch Reception at SMU ---

01:45pm - 02:30pm

Point-of-interest recommendation in location-based social networks (PDF)
Irwin King, The Chinese University of Hong Kong, Hong Kong

02:30pm - 03:15pm

Learning-based approaches for link discovery given unlabelled data (PDF)
Shou-De Lin, National Taiwan University, Taiwan

03:15pm - 03:45pm

--- Coffee Break ---

03:45pm - 04:15pm

Real-time bursty topic detection on social media
Feida Zhu, Singapore Management University

04:15pm - 04:45pm

More effective distributed ML via a stale synchronous parallel parameter server (PDF)
Qirong Ho, Carnegie Mellon University, USA

04:45pm - 05:15pm

Large-scale social identity linkage via heterogeneous behavior modeling (PDF)
Siyuan Liu, Carnegie Mellon University, USA

05:15pm - 06:00pm

Poster & Demo Session
Venue: Li Ka Shing Library, Quiet Corner

06:00pm - 09:00pm

Dinner Reception
Venue: Li Ka Shing Library, Quiet Corner

Friday, 28 Feb 2014
Venue: University Hall Auditorium, Lee Kong Chian Wing, Level 2, 21 Lower Kent Ridge Road, S(119077), NUS

09:00am - 10:00am

On the algorithmic and system interface of big learning
Eric Xing, Carnegie Mellon University, USA

10:00am - 10:30am

--- Coffee Break ---

10:30am - 11:15am

Bayesian approaches to describing complex problems
Kerrie Mengerson, Queensland University of Technology, Australia

11:15am - 12:00nn

Active learning for probabilistic models (PDF)
Wee Sun Lee, National University of Singapore

12:00nn - 01:00pm

--- Lunch Reception at University Hall ---

01:00pm - 01:30pm

Mining viewpoints from online forums
Jing Jiang, Singapore Management University

01:30pm - 02:00pm

Online learning for big data and living analytics (PDF)
Steven Hoi, Nanyang Technological University

02:00pm - 02:30pm

--- Coffee Break ---

02:30pm - 05:30pm

Tutorial: Successful data mining in practice
Richard De Veaux, Williams College, USA

05:30pm - 05:45pm

Closing Remarks




This workshop is free for all participants from academic institutions.

All other participants are required to pay a registration fee of S$150 (excluding 7% GST). The registration will include entry to all workshop activities, including dinner reception. Enjoy a group discount of 20% for 5 or more registrations from the same billing organisation!


Online Registration is closed.





Organizing Committee · Visitors and Participants · Overview · Activities · Venue

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