III: Workshop support for meeting on algorithms for modern massive data sets, MMDS 2010

Stanford University, Stanford CA

Investigators

Abstract

The proposal is a request for funds to support the biennial MMDS meetings on Algorithms for Modern Massive Data Sets. The goals of these meetings are: (1) to explore novel techniques for modeling and analyzing massive, high-dimensional, and nonlinearly-structured scientific and internet data sets; and (2) to bring together computer scientists, statisticians, mathematicians, and data analysis practitioners to promote cross-fertilization of ideas. The meetings will occur in the wake of two related meetings in 2006 and 2008 that addressed similar topics. Both MMDS 2006 and MMDS 2008 were an enormous interdisciplinary success, and they clearly highlighted the need for a regular meeting forum to bring together junior and senior researchers from a range of backgrounds to address the challenging foundational problems that will be faced in upcoming years as increasingly large and complex data sets are generated in a wide range of application domains. The proposed meetings will capitalize on these past successes and extend the MMDS series into a more regular series of meetings to address algorithmic, statistical, and computational aspects of modern massive data set analysis. The topics covered by MMDS address fundamental algorithmic questions underlying much of the recent work in large-scale data analysis. In addition, topics of interest at MMDS include data problems ranging from better search and ranking at internet sites to improved methods for extracting structure in genetics applications to analyzing biomedical images for improved disease detection. Progress on these fronts will be fueled by junior researchers as well as researchers from a wide range of application areas. Thus, every effort was be made to include junior researchers, including women and minorities, at past meetings and to disseminate the information presented at the meetings to people who were not able to attend. This will be continued at future meetings. For more information, please see the meeting webpage: http://mmds.stanford.edu/