MSCS Statistics and Data Science Seminar

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Statistics and Data Science Seminar - Spring 2019

Usually meets Wednesday at 4:00 pm in SEO 636.

Date	Speaker	Title
January 16
January 23
January 30
February 6
February 13
February 20 (4:00 pm; 636 SEO)	Subhashis Ghoshal North Carolina State University	Posterior Contraction and Credible Sets for Filaments of Regression Functions
February 27 (4:00 pm; 636 SEO)	William Li Shanghai Advanced Institute of Finance	Using Prior Information for Intelligent Factor Allocation and Design Selection
March 6 (4:00 pm; 636 SEO)	Yue Niu University of Arizona	A Super Scalable Algorithm for Short Segment Detection
March 13 (4:00 pm; 636 SEO)	Hani Aldirawi University of Illinois at Chicago	Identifying Appropriate Probabilistic Models for Sparse Discrete Data
March 20 (4:00 pm; 636 SEO)	Mengjia Yu UIUC	Finite sample change point inference and identification for high-dimensional location-shift
March 27	No seminar	Spring Break
April 3 (4:00 pm; 636 SEO)	Marco Ferreira Virginia Tech	Dynamic Multiscale Spatiotemporal Models for Multivariate Gaussian Data
April 10 (4:00 pm; 636 SEO)	Jane Qian Abbvie	Overview of ICH E9(R1): Estimands and Sensitivity Analysis in Clinical Trials
April 17 (3:00 pm; 636 SEO)	Junhui Wang City University of Hong Kong	A smooth collaborative recommender system
April 17 (4:00 pm; 636 SEO)	Yehua Li University of California at Riverside	Spatially Dependent Functional Data: Covariance Estimation, Principal Component Analysis, and Kriging
April 24 (4:00 pm; 636 SEO)	Wenhui Sheng Marquette University	Sufﬁcient dimension folding via distance covariance
May 1 (4:00 pm; 636 SEO)	Solomon Harrar University of Kentucky	Weak Dependence Conditions for High-Dimensional Inference: Applications to Group Comparisons
May 13 (3:00 pm; 636 SEO)	Abhyuday Mandal University of Georgia	EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments with Both Quantitative and Qualitative Factors
May 13 (4:00 pm; 636 SEO)	William Li Shanghai Advanced Institute of Finance	A Class of New Particle Swarm Optimization Algorithms and Applications to Model Discriminating Designs

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