{"129751":{"#nid":"129751","#data":{"type":"news","title":"Georgia Tech Researchers Awarded Best Paper at SIAM International Conference on Data Mining","body":[{"value":"\u003Cp class=\u0022p1\u0022\u003EGeorgia Institute of Technology researchers Dongryeol Lee, Alexander G. Gray and Richard Vuduc, from the College of Computing, were awarded Best Paper at the SIAM International Conference on Data Mining April 26 for their paper \u201cA Distributed Kernel Summation Framework for General-Dimension Machine Learning.\u201d\u0026nbsp;\u003C\/p\u003E\u003Cp class=\u0022p2\u0022\u003EKernel summations are a ubiquitous key computational bottleneck in many data analysis methods. The paper proposes a hybrid MPI\/OpenMP kernel summation framework for scaling many popular data analysis methods. Advantages to the approach include utilizing the platform-independent C++ code base that utilizes standard protocols such as MPI and OpenMP; using the template code structure that uses any multidimensional binary trees and any approximation schemes that may be suitable for high-dimensional problems; and having extendibility to a large class of problems that require fast evaluations of kernel sums.\u003C\/p\u003E\u003Cp class=\u0022p2\u0022\u003E\u201cResearchers have previously parallelized kernel summations in the context of simulations,\u201d says Dongryeol Lee, a Ph.D. candidate in Computer Science. \u201cBut this paper is the first serious effort in parallelizing kernel summations in the context of data mining with potentially high-profile scientific applications.\u201d\u003C\/p\u003E\u003Cp class=\u0022p2\u0022\u003EIn data mining, kernel summations appear in popular so-called kernel methods which can model complex, nonlinear structures in data. The richer expressiveness of the methods comes with the drawback of requiring many data points and hence more computational power for crunching collected data, according to Lee. The collected data in some cases must be stored on multiple machines.\u003C\/p\u003E\u003Cp class=\u0022p4\u0022\u003EFrom the data mining community, Lee says this work is the first to utilize algorithmic techniques in both high performance computing, computer\u0026nbsp;science, computational physics, computational geometry, and approximation theory in a general framework.\u003C\/p\u003E\u003Cp class=\u0022p4\u0022\u003EKernel summations drive algorithms in application areas such as finance, astronomy, and medical science.\u0026nbsp;\u003C\/p\u003E\u003Cp class=\u0022p4\u0022\u003ELee notes some examples: \u201cFraudulent financial transactions can be detected more quickly using fast kernel summations. Astronomy uses the algorithms to predict redshift of many galaxies and stars, which can shed light onto the ultimate fate of the universe. Medicine uses fast kernel summation algorithms in automated early detection of cancer that can save human lives.\u0022\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Institute of Technology researchers Dongryeol Lee, Alexander G. Gray and Richard Vuduc, from the College of Computing, were awarded Best Paper at the SIAM International Conference on Data Mining April 26 for their paper \u201cA Distributed Kernel Summation Framework for General-Dimension Machine Learning.\u201d\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":"","uid":"27592","created_gmt":"2012-05-10 15:21:00","changed_gmt":"2016-10-08 03:12:13","author":"Joshua Preston","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2012-05-10T00:00:00-04:00","iso_date":"2012-05-10T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"groups":[{"id":"1304","name":"High Performance Computing (HPC)"}],"categories":[],"keywords":[{"id":"33291","name":"data analysis"},{"id":"33301","name":"data analytics"},{"id":"9168","name":"data mining"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EJoshua Preston\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022mailto:jpreston@cc.gatech.edu\u0022\u003Ejpreston@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E678-231-0787\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":["jpreston@cc.gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}