On a class of interacting randomly reinforced processes
Sponsor(s):
Statistical Science
Friday, October 28, 2016
3:30 pm - 4:30 pm
Sonia Petrone, Bocconi University
Sparse Graphs via CRMs and Advances in the Associated MCMC
Sponsor(s):
Statistical Science
Friday, November 04, 2016
3:30 pm - 4:30 pm
Emily Fox, University of Washington
Macroeconomic Predictions with Big Data: The Illusion of Sparsity
Sponsor(s):
Statistical Science
Friday, November 11, 2016
3:30 pm - 4:30 pm
Domenico Giannone, Federal Reserve Bank of New York
Bayesian Predictive Density Combinations for Exchange Rate Models
Sponsor(s):
Statistical Science
Friday, November 18, 2016
3:30 pm - 4:30 pm
Knut Are Aastveit, Norges Bank
Food Culture I: Chef's Table - Bottura
Sponsor(s):
Romance Studies
Wednesday, January 25, 2017
6:30 pm - 8:00 pm
Vishesh Karwa - Harvard University
Sponsor(s):
Statistical Science
Friday, January 27, 2017
3:30 pm - 4:30 pm
Vishesh Karwa - Harvard University
Bayesian Covariance Estimation with Applications in High-throughput Biology
Sponsor(s):
Statistical Science
Friday, February 03, 2017
3:30 pm - 4:30 pm
Alexander Franks, University of Washington
A Bayesian Multivariate Functional Dynamic Linear Model
Sponsor(s):
Statistical Science
Friday, February 10, 2017
3:30 pm - 4:30 pm
Dan Kowal - Cornell
Bayesian Nonparametric Modeling of Network Data
Sponsor(s):
Statistical Science
Friday, February 17, 2017
3:30 pm - 4:30 pm
Daniele Durante - Universita Degli Studi Di Padova
Bayesian Deep Learning and Black Box Variational Inference
Sponsor(s):
Statistical Science
Friday, February 24, 2017
3:30 pm - 4:30 pm
Rajesh Ranganath, Princeton
Machine Learning/Statistics Seminar
Sponsor(s):
Machine Learning, Bass Connections-Information, Society & Culture, Biostatistics and Bioinformatics, Computer Science, Electrical and Computer Engineering (ECE), Information Initiative at Duke (iiD), Mathematics, and Pratt School of Engineering
Friday, March 03, 2017
3:30 pm - 4:30 pm
Harry Crane
Markov process models for time-varying networks: basic theory and practical limitations
Sponsor(s):
Statistical Science
Friday, March 03, 2017
3:30 pm - 4:30 pm
Harry Crane - Rutgers University
Monte Carlo estimates with user-specified relative error
Sponsor(s):
Statistical Science
Friday, March 10, 2017
3:30 pm - 4:30 pm
Mark Huber, Claremont McKenna College
Sparse and time-varying covariance modeling
Sponsor(s):
Statistical Science
Monday, March 20, 2017
3:30 pm - 4:30 pm
Hedibert Freitas Lopes, Insper
NonGaussian Multivariate Time Series Modeling
Sponsor(s):
Statistical Science
Monday, March 20, 2017
3:30 pm - 4:30 pm
Refik Soyer, George Washington University
Tempered Particle Filtering
Sponsor(s):
Statistical Science
Friday, March 24, 2017
3:30 pm - 4:30 pm
Frank Schorfheide, Penn Arts & Sciences
Cross-country macro evidence on the effectiveness of unconventional monetary policies in a low interest rate environment
Sponsor(s):
Statistical Science
Monday, March 27, 2017
3:30 pm - 4:30 pm
Jouchi Nakajima - Bank for International Settlements
Unique representations of sparse factor models
Sponsor(s):
Statistical Science
Friday, March 31, 2017
3:30 pm - 4:30 pm
Sylvia Kaufmann (Gerzensee, Swiss Ntl Bank, Economics & Finance)
A simple, fast sampler for simulating spatial data and other Markovian data structures
Sponsor(s):
Statistical Science
Wednesday, April 05, 2017
3:30 pm - 4:30 pm
Andee Kaplan - Iowa State University
TAMID Presents: Wayne Kimmel- Entrepreneurship, Networking, and Developing Mutually Beneficial Relationships
Sponsor(s):
TAMID
Wednesday, April 05, 2017
6:00 pm - 7:00 pm
Globalism vs. Nationalism
Sponsor(s):
International Association (IA)
Wednesday, April 05, 2017
7:30 pm - 9:00 pm
Machine Learning/Statistics Seminar
Sponsor(s):
Machine Learning, Bass Connections-Information, Society & Culture, Biostatistics and Bioinformatics, Computer Science, Electrical and Computer Engineering (ECE), Information Initiative at Duke (iiD), Mathematics, and Pratt School of Engineering
Friday, April 07, 2017
3:30 am - 4:30 am
Shane Jensen
Urban Analytics: A Case Study in Philadelphia
Sponsor(s):
Statistical Science
Friday, April 07, 2017
3:30 pm - 4:30 pm
Shane Jensen, The Wharton School, University of Pennsylvania
Bayesian nonparametric inference for discovery probabilities: credible intervals and large sample asymptotics
Sponsor(s):
Statistical Science
Friday, April 14, 2017
3:30 pm - 4:30 pm
Julyan Arbel, Inria Grenoble-Rhone-Alpes
A Multilevel Bayesian Approach for Modeling the Time-to-Serve in Professional Tennis
Sponsor(s):
Statistical Science
Wednesday, April 19, 2017
3:30 pm - 4:30 pm
Jim Albert, Bowling Green State University
Using Data Science in Educationand Research: A Practioner Perspective
Sponsor(s):
Statistical Science
Monday, April 24, 2017
3:30 pm - 4:30 pm
Sudipta Dasmohapatra, NCSU
A Bayesian Item Response Theory Approach to Estimating Survey Mode Effects
Sponsor(s):
Statistical Science
Wednesday, April 26, 2017
3:30 pm - 4:30 pm
Lou Mariano, RAND
Encounters with imprecise probabilities
Sponsor(s):
Statistical Science
Friday, September 01, 2017
3:30 pm - 4:30 pm
James Berger, Duke University
Change-point detection for locally dependent data
Sponsor(s):
Statistical Science
Friday, September 08, 2017
3:30 pm - 4:30 pm
Hao Chen, University California, Davis
Multi-scale Classification using Localized Spatial Depth
Sponsor(s):
Statistical Science
Friday, September 15, 2017
3:30 pm - 4:30 pm
Subhajit Dutta
Global-Local Priors for Small Area Estimation
Sponsor(s):
Statistical Science
Friday, September 22, 2017
3:30 pm - 4:30 pm
Malay Ghosh, University of Florida
Information Recovery in Shuffled Graphs via Graph Matching
Sponsor(s):
Statistical Science
Friday, September 29, 2017
3:30 pm - 4:30 pm
Vince Lyzinski, Johns Hopkins University
Unbiased Markov chain Monte Carlo with couplings
Sponsor(s):
Statistical Science
Friday, October 13, 2017
3:30 pm - 4:30 pm
Pierre Jacob, Harvard University
A projection-based approach for spatial generalized linear mixed models
Sponsor(s):
Statistical Science
Friday, October 20, 2017
3:30 pm - 4:30 pm
Murali Haran, Penn State
Bayesian Approaches for Dynamic Model Selection: two contributions
Sponsor(s):
Statistical Science
Friday, October 27, 2017
3:30 pm - 4:30 pm
Michele Guindani, University of California, Irvine
An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity Analysis via Empirical Processes
Sponsor(s):
Statistical Science
Friday, November 03, 2017
3:30 pm - 4:30 pm
Hani Doss, University of Florida
Meta-Analysis With Multiple Imputation: Constructing Data Banks for Hard-To-Study Populations
Sponsor(s):
Statistical Science
Friday, November 10, 2017
3:30 pm - 4:30 pm
Elly Kaizar, Ohio State
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