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THE
FIELDS INSTITUTE FOR RESEARCH IN MATHEMATICAL SCIENCES
Thematic
Program on Statistical Inference, Learning, and Models for Big
Data, January to June, 2015
Friday
June 12 & Saturday June 13, 2015
Closing Conference: Statistical and Computational Analytics
for Big Data
Held
at Dalhousie University
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Organizing
Committee
Hugh
Chipman (Chair) : hugh.chipman (at) gmail.com
Stan Matwin
Nancy Reid
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On-line
Registration
Registration fees:$75 (regular rate), $30 (students and PDF)
Online registration open to end of June 4. Onsite registration available
during workshop: $100 (regular rate) $50 (students and PDF)
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Presented jointly with the Institute for Big Data Analytics (IBDA) at Dalhousie
University and sponsored by the Canadian Statistical Sciences Institute and
the Atlantic Association for Research in the Mathematical Sciences, this workshop
will give an overview of highlights of the thematic program on Statistical
Inference, Models and Learning for Big Data, will showcase current IBDA student
projects and will present research at IBDA on text mining, high-performance
computing, visualization, bioinformatics, and privacy.
Funding support:
Students and Postdoctoral Fellows may apply for travel funding. When registering,
select "Funding Application Form" and complete that form. Deadline:
Extended to May 19
Conference Location:
Computer Science Auditorium
Goldberg Computer Science Building
6050 University Avenue, Dalhousie University
Schedule Overview:
Friday June 12
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9:00 - 9:10 |
Opening Remarks |
9:10 - 9:50 |
Hugh Chipman, Acadia University, Statistical
and computational challenges in networks and cybersecurity |
9:50 - 10:30 |
Jean-Francois Plante, HEC Montréal,
Challenges, Tools and Examples for
Big Data Inference |
10:30 - 11:00 |
Coffee |
11:00 - 11:40 |
Lisa Lix, University of Manitoba, How
Big Data and Causal Inference Work Together in Health Policy |
11:40 - 12:20 |
Stephanie Shipp, Virginia Tech, Policy
meets Social and Decision Informatics |
12:20 - 1:30 |
Lunch |
1:30 - 2:10 |
Stan Matwin, Dalhousie University,
Big Data meets Big Water: Mining
Ocean Vessel Trajectory Data |
2:10 - 2:50
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Evangelos Milios, Dalhousie University,
Exploiting Semantic Analysis of Documents
for the Domain User |
2:50 - 3:30 |
Andrew Rau-Chaplin, Dalhousie University,
Scaling up to Big Data: Algorithmic
Engineering + HPC |
3:30 - 4:00 |
Coffee |
4:00 - 4:40 |
Rosane Minghim, Dalhousie University/University
of São Paulo, Multidimensional
Projections and Tree-based Techniques for Visualization and Mining |
4:40 - 5:20
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Rob Beiko, Dalhousie University, Microbial
genomics for rapid investigation of infectious disease |
5:30 - 7:00
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Reception |
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Saturday June 13
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9:00 - 10:20 |
Panel discussions on training for data science
at the undergraduate and graduate levels. |
10:20 - 10:40 |
Coffee |
10:40 - 11:20 |
Roger Grosse, University of Toronto,
Highlights from the deep learning
workshop |
11:20 - 12:00 |
Einat Gil, University of Toronto, Learning
about Big Data among Secondary School Students in a technology-supported
collaborative learning environment |
Accommodations:
This workshop is immediately before the annual
meeting of the Statistical Society of Canada. Consult their
accommodations page for links to accommodations in the area.
Confirmed Speakers:
Hugh
Chipman, Acadia
Jean-François Plante,HEC
Lisa Lix, U Manitoba
Stephanie Shipp, Virginia Tech
Stan Matwin, IBDA
Evangelos Milios, Dalhousie
Andrew Rau-Chaplin, Dalhousie
Rosane
Mingham, Dalhousie University / University of São Paulo
Rob
Beiko, Dalhousie
Roger
Grosse, U Toronto
Einat
Gil, U Toronto
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