DIMACS Workshop on Analysis of Information from Diverse Sources

May 16 - 17, 2013
DIMACS Center, CoRE Building, Rutgers University

Organizers:
Min-ge Xie, Rutgers University, mxie at stat.rutgers.edu
Abel Rodriguez, University of California
Presented under the auspices of the Special Focus on Information Sharing and Dynamic Data Analysis and the Department of Statistics, Rutgers University.

Workshop Program:

 
Thursday, May 16, 2013  

 8:30 -  9:00  Breakfast & Registration    

 9:00 -  9:05  Welcome
               Minge Xie, Rutgers University
               Abel Rodriguez, University of California

 9:05 -  9:15  Opening Remarks
               Jim Masschaele, School of Arts and Sciences/Rutgers University
               Regina Liu, Statistics/Rutgers University

 9:15 -  9:50  Text Network
               David Banks, Duke University     

 9:50 - 10:25  Inferring Regulatory Networks by Combining 
               Perturbation Screens and Steady State Gene Expression Profiles 
               George Michailidis, University of Michigan

10:25 - 10:40  Break   

10:40 - 11:15  Combining Single and Two Group Outcome 
               Risks/Comparisons from Multiple Studies of Safety
	       Nick Jewell, UC-Berkeley

11:15 - 11:50  Bayesian Network Meta-Analysis for 
               Unordered Categorical Outcomes With Incomplete Data 
               Chris Schmid, Brown University

11:50 - 12:25  Confidence distribution approaches to efficient 
               meta-analysis of heterogeneous studies 
               Dungang Liu, Yale University 

12:25 -  1:35  Lunch  

 1:35 -  1:45  Director's Welcome 
               Rebecca Wright, Director of DIMACS		 

 1:45 -  2:20  Development of Power Priors for Incorporating 
               Historical Data with Applications
	       Ming-hui Chen, University of Connecticut

 2:20 -  2:55  Efficiency of Bayesian procedures and the
               frequentist-Bayes connection in some high dimensional problems 
	       Natesh Pillai, Harvard University 

 2:55 -  3:30  One-shot learning and big data with n=2
               Lee Dicker, Rutgers University

 3:30 -  3:50  Break

 3:50 -  4:25  Unsupervised learning of compositional sparse code for natural image representation
	       Yingnian Wu, UCLA

 4:25 -  5:00  Design and Analysis for Multifidelity Computer Experiments
               Ying Hung, Rutgers University

 5:30          Workshop Dinner  

Friday, May 17, 2013  

 8:15 -  8:50  Breakfast and Registration   

 8:50 -  9:25  Genetic Studies of Multivariate Traits
	       Heping Zhang, Yale University 

 9:25 - 10:00  Combining information from different sources: A resampling approach
               Soumen Lahiri, North Carolina State University 

10:00 - 10:35  Nonparametric inference for meta-analysis with fixed, unknown,
               study-specific parameters:  A resampling of confidence distributions approach
	       Brian Claggett, Harvard University

10:35 - 10:45  Break  

10:45 - 11:20  Bayesian Inference for General Gaussian Graphical 
               Models With Application to Multivariate Lattice Data
               Abel Rodriguez, UC-Santa Cruz

11:20 - 11:55  Scaling It Up: Stochastic Graphical Model Determination
               under Spike and Slab Prior Distributions
               Hao Wang, University of South Carolina

11:55 - 12:30  A Bayesian Nonparametric Approach for Spatial Point Processes
               Gavino Puggioni, University of Rhode Island

12:30 -  1:05  Revolutionizing Policy Analysis Using "Big Data" Analytics
               Siddhartha R. Dalal, RAND Corporation, Columbia University & DIMACS, Rutgers 

 1:05 -  1:15  Closing Remarks/Discussion
   
 1:15 -  2:30  Lunch

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Document last modified on May 13, 2013.