Workshop on Statistical Issues in Analyzing Information from Diverse Sources

May 6 - 7, 2010
CICCADA Center, CoRE Building, Rutgers University

Organizers:
Tami Carpenter, Rutgers University, tcar at dimacs.rutgers.edu
Minge Xie, Rutgers University, mxie at stat.rutgers.edu
Presented under the auspices of the The Homeland Security Center for Command, Control, and Interoperability Center for Advanced Data Analysis (CCICADA) and the Department of Statistics, Rutgers University. 
Thursday, May 6, 2010

 8:30 -  9:00  Breakfast and registration

 9:00 -  9:05  Welcome
               Minge Xie, Rutgers University

 9:05 -  9:15  Opening remarks and CCICADA overview
               Tami Carpenter, Rutgers University

 9:15 -  9:20  Opening remarks
               Mike Pazzani, Rutgers University
 
 9:20 - 10:20  Opening Keynote: The Bayesian Approach to Combination of Information
               Jim Berger, Duke University

10:20 - 10:35  Break 

10:35 - 11:10  Using Diverse Types of Statistical Evidence
               Robert Bell, AT & T Labs Research

11:10 - 11:45  Bayesian Uncertainty Quantification for Inverse Problems Using a Multiscale Hierarchical Model
               Bani Mallick, Texas A&M University

11:45 - 12:20  Evaluating the Repeatability of Two Studies of a Large Number of Objects: Modified Kendall Rank-order Association Test
               Tian Zheng, Columbia University

12:20 -  1:20  Lunch 

 1:20 -  1:55  Anonymization and Uncertainty
               Graham Cormode, AT&T Labs - Research

 1:55 -  2:30  Collective Graph Identification
               Lise Getoor, University of Maryland

 2:30 -  3:05  Ranking Genes, Ranking Documents, Ranking Drug Candidates: A Unified Machine Learning Approach  
               Shivani Agarwal, MIT

 3:05 -  3:25  Break 

 3:25 -  4:00  Mitigating Manhole Events in New York City Using Machine Learning
               Cynthia Rudin, MIT

 4:00 -  4:35  Bayesian Combining of Information from Sensors: Applications to Nuclear
               Sid Dalal, RAND Corporation

 4:35 -  5:10  Integrating Diverse Biological Data Sources for Improved Gene Function Prediction
               Chandan Reddy, Wayne State University

 5:30          Workshop Dinner

Friday, May 7, 2010

 8:30 -  9:00  Breakfast

 9:00 - 10:00  Opening Keynote: Product Formulas for Positive Functions and Applications to Network Data 
               Peter Jones, Yale University

10:00 - 10:35  Two Newly Developed Quantitative Methods for Meta Analysis
               L. J. Wei, Harvard University

10:35 - 10:55  Break

10:55 - 11:30  A General Framework for Combining Information and an Application to Incorporating Expert Opinions
               Regina Liu, Rutgers University

11:30 - 12:05  Combining Multiple Data Sources for Comparative Effectiveness
               Sharon-Lise Normand, Harvard University

12:05 -  1:00  Lunch

 1:00 -  1:35  How to Find a Correlation When None Exists
               Abraham Wyner, University of Pennsylvania and Larry Shepp, Rutgers University
 
 1:35 -  2:10  Google Ads Quality - An Real-Life Statistical Problem for Multi-Layered Systems
               Yunkai Zhou, Google

 2:10 -  2:45  Architectures for Inferences from Multiple Sources
               Paul Kantor, Rutgers University

 2:45 -  3:00  Closing Remarks/Discussion
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Document last modified on May 4, 2010.