January 19-20, 2018
Abstract:
In recent years, the availability of high-throughput data from genomic, finance, environmental, marketing (among other) applications has created an urgent need for methodology and tools for analyzing high-dimensional data. The explosion of data, due to advances in science and information technology, has left almost no field untouched. It is not uncommon to see datasets of sizes in terabytes and/or with millions of covariates. The field of non-parametric and semi- parametric statistics is quickly evolving and expanding to adapt to the challenges posed by big data. A variety of new techniques have been developed. Some of these techniques leverage the recent developments in the parallel and distributed computing, while others rely on appropriate sparsity assumptions to reduce the effective number of covariates. In addition, recent work has shown that many of these methodologies drastically reduce computation time while retaining the optimality properties of the standard non-parametric and semiparametric methods. Despite important breakthroughs in the last few years, a lot of unanswered questions remain. In an effort to address this, the proposed workshop will bring together individuals who have done path-breaking work in this field.
2018 Conference Programs
Guest Speakers
Moulinath Banerjee, Professor of Statistics, University of Michigan, “Intelligent Sampling for Estimating Change Points in Very Long Sequential Data”- Video
Guang Cheng, Purdue University, “Can We Do Statistical Inference in a Non-Asymptotic Way?”- Video
Subhashis Ghoshal, North Carolina State University ,“Bayesian Analysis of Brain Connectome Data for Studying Alzheimer Disease”- Video
Yanyuan Ma, Pennsylvania State University, “On Estimation of General Index Model for Survival Data” – Video
Hans-Georg Mueller, Professor of Statistics, University of California at Davis, “Frechet Regression and Applications”- Talk Video
Annie Qu, Professor of Statistics, University of Illinois at Urbana-Champaign, “Cluster Analysis of Longitudinal Profiles with Subgroups”- Video
Bodhisattva Sen, Columbia University, “Spatial Adaptivity in Trend Filtering”- Video
Wei Biao Wu, Professor of Statistics, University of Chicago, “Testing for Trends in High-dimensional Time Series”- Video
Cun-Hui Zhang, Rutgers University, “Simultaneous Bootstrap Inference with High-Dimensional Data”- Video
Organizers
Dr. Kshitij Khare and Dr. Rohit Patra
Sponsors
Info Tech
UF Informatics Institute
UF Department of Statistics