Workshop on Dimension Reduction and High-dimensional Inference: Theory and Applications

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The workshop on "Dimension Reduction and High-Dimensional Inference: Theory and Applications" will be held on January 17-18, 2014, on the campus of the University of Florida, Gainesville, FL, USA. The project will provide travel support for 25 young researchers and two invited speakers. The field of dimension reduction has a long history, but the overarching aim is to reduce the dimension of a family of multivariate random vectors in such a way that the information deemed relevant is preserved. Today, with high-throughput technologies and fast computing, high dimensionality in data is pervasive. Dimension reduction is now a prevalent theme throughout the applied sciences, including genetics, food science, biomedical engineering, economics and computer science. The area of dimension reduction is quickly evolving and expanding to adapt to this new reality. In this workshop, twelve distinguished individuals who work in dimension reduction and high-dimensional inference will review the current state of the field and present their recent work. A number of young researchers will participate in the workshop and present their work in poster sessions.Dimension reduction offers an appealing avenue for dealing with high dimensional problems. In effect it transforms a high dimensional data set to a low dimensional one by identifying and combining a small set of important variables which give as much or nearly as much information as the original large set of variables. Then one can build models and perform estimation or prediction based on the low dimensional data set. Many existing models and approaches, which do not apply to high dimensional data, can be applied to the reduced low dimensional data. In addition, effective reduction in dimension often makes it possible to visualize the data, which can facilitate subsequent model development. Dimension reduction is now an active research area, but many unsolved problems remain. The workshop provides an excellent opportunity for established researchers in the field, as well newcomers, to discuss the significant developments that have taken place recently; to discuss what works and what does not; and to identify important problems and new research directions.