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Stochastic Modeling and Computational Statistics


  1. 40 minutes for each talk + 10 minutes for discussion.
  2. The talk should be accessible to all grad students who have completed 1 year of the program.
  3. Informal style. For instance, chalk and blackboard talks are welcome.
  4. Interruptions during the talk are welcome but they should only be for clarifications; longer questions are to be left to the discussion period.
  5. Unpublished work may not be shared or discussed outside the group without the permission of the speaker/author.
  6. While a large proportion of the talks may be related to stochastic modeling and computing, a much broader list of topics have also been discussed in this series.
Date Speaker Topic
August 26 Runze Li Error variance estimation for high-dimensional regression
September 2 Rick Gilmore (Co-Dir. of digital data library, PSU) Donald Rumsfeld and the future of big data behavioral science
September 9 Ethan Fang Optimal Two Stage Adaptive Enrichment Designs for Randomized Trials 
Using Sparse Linear Programming
September 16 Xiaoyue Maggie Niu An "old" dynamic social network model, some recent developments, and lessons learned
September 23 Vesna Gotovac, Faculty of Science, University of Split, Croatia Assessing dissimilarity of random sets
September 30 Jaewoo Park MCMC Algorithms for Models with Intractable Normalizing Functions
October 7 Bharath Sriperumbudur Shrinkage Estimation in RKHS
October 14 Angie Wolfgang, PSU Astronomy Hierarchical Bayesian Modeling of the Period-Dependent Diversity of Small-Planet Compositions
October 21 Jenny Wadsworth, Lancaster University, UK Progress and challenges in spatial extremes
October 28 Lynn Lin Clustering with Hidden Markov Model on Variable Blocks
November 4 Guangqing Chi, Rural Sociology; Dir of Comp and Spatial Analysis Core The Power of Computational and Spatial Analysis for Population Research in the Era of Big Data
November 11 Junli Lin Testing Independence Using Kernel Methods and Ranks
November 18 Marzia Angela Cremona, PSU Stats postdoc Discovering motifs in "Omics" signals using local clustering of curves
November 25 Thanksgiving break  
December 2 Om Thakkar, Computer Science and Engineering, Penn State Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing

A look back at previous SMAC TALKS.