PPT-Multidimensional Scaling by Deterministic Annealing with It

Majorization Algorithm SeungHee Bae Judy Qiu and Geoffrey Fox SALSA group in Pervasive Technology Institute at Indiana University Bloomington Outline Motivation Background and Related Work. photodetachment. of anionic copper carbonyl clusters in argon matrices. Ryan M. Ludwig, Michael E. Goodrich, . David T. Moore. Chemistry Department, Lehigh University. 69. th. ISMS, Univ. Illinois Urbana-Champaign. By . Rohit. Ray. ESE 251 . The Problem. Most . minimization (maximization) strategies . work to find the nearest local minimum. Trapped at local . minimums (maxima). Standard strategy. Generate trial point based on current estimates. input data are ranks: most similar pair AB. <. CB. <. AC most different pair, or input data are rating scales: (very similar 1. . .9 very different), but we don't believe in assuming interval level property of data.. Jong Youl Choi, Judy . Qiu. , Marlon Pierce, and Geoffrey Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. S. A. L. S. A. project. . http://. salsahpc.indiana.edu. Community Grids Lab.. Indiana University, Bloomington. Seung-Hee Bae. Contents. Multidimensional Scaling (MDS). Scaling by MAjorizing a COmplicated Function (SMACOF). Parallelization of SMACOF. Performance Analysis. Kruskal. , Joseph B. and Myron Wish (1978), . Multidimensional Scaling. , Beverly Hills: Sage. . Great primer to get you started..  Green, Paul E., Frank J. . Carmone. Jr., and Scott M. Smith (1989), . Jong Youl Choi, Judy . Qiu. , Marlon Pierce, and Geoffrey Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. S. A. L. S. A. project. . http://. salsahpc.indiana.edu. Daniel Paden Tomasello. Simulated Annealing Algorithm. An approximation algorithm used for global optimization. . In my model, simulated annealing is used to help a robot, which may only detect surrounding elevations, find the highest elevation. (Local Search). and . Robust . Scalable Data mining . for . the Data Deluge . Petascale Data Analytics: Challenges, and Opportunities (PDAC-11. ). Workshop at SC11 Seattle. November 14 2011. Geoffrey Fox. gcf@indiana.edu. Annealing . Dimension Reduction. and Biology. Indiana University. Environmental Genomics. April 20 2012. Geoffrey Fox. gcf@indiana.edu. . . http://www.infomall.org. . http://www.futuregrid.org. Rohit. Ray. ESE 251 . The Problem. Most . minimization (maximization) strategies . work to find the nearest local minimum. Trapped at local . minimums (maxima). Standard strategy. Generate trial point based on current estimates. to . LC-MS Data Analysis.  . October 7 2013. . IEEE . International Conference on Big Data 2013 (IEEE . BigData. 2013. ). Santa Clara CA. Geoffrey Fox, D. R. Mani, . Saumyadipta. . Pyne. gcf@indiana.edu. Scaling. Maya Smith(Winston Salem State University), Anthony Scott (Winston Salem State University), Mentor: Supun . Kamburugamuve . (Indiana University) Principal Investigator: Dr. Geoffrey Fox (Indiana University. Ali S. Hadi and . Rida. Moustafa. ahadi@aucegypt.edu. ali-hadi@cornell.edu. www.aucegypt.edu/faculty/hadi. Outline of the Talk. Introduction. 2. Types of . Centering and/or Scaling. . Effects of Centering and/or Scaling.