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Activity Details

588 Wed, 8/2/2017, 2:00 PM - 3:50 PM CC-337
Statistical Learning: Clustering — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): John Nagorski, Rice University
2:05 PM Randomized SUP: a Clustering Algorithm for Large-Scale Data — Shang-Ying Shiu, Department of Statistics, National Taipei University ; Ting-Li Chen, Institute of Statistical Sciences, Academia Sinica ; Yen-Shiu Chin, Institute of Statistical Sciences, Academia Sinica ; Wush Wu, Department of Electrical Engineering, National Taiwan University
2:20 PM Multi Level Clustering Technique Leveraging Expert Insight — Sudhanshu Singh, IBM India Pvt. ltd. ; Ritwik Chaudhuri, IBM India Pvt. ltd. ; Manu Kuchhal, IBM India Pvt. ltd. ; Sarthak Ahuja, IBM India Pvt. ltd. ; Gyana Parija, IBM India Pvt. ltd.
2:35 PM Variable Selection in K-Means Clustering — Nicholas Scott Berry, Iowa State University ; Ranjan Maitra, Iowa State University
2:50 PM Two-Layer Heterogeneity Model for Massive Data — Ching-Wei Cheng, Purdue University ; Guang Cheng, Purdue
3:05 PM Topological Probabilistic Classification (TopProC) — Fairul Mohd-Zaid, Air Force Research Lab ; Christine Schubert Kabban, Air Force Institute of Technology
3:20 PM Poisson-Kernel Based Clustering on the Sphere: Convergence Properties, Initialization Rules and a Method of Sampling — Mojgan Golzy, State University of New York At Buffalo ; Marianthi Markatou, University at buffalo, Department of Biostatistics ; Alexander Foss, State University of New York at Buffalo
3:35 PM A One-Class Convex Hull Peeling Method for Outlier Detection — Waldyn Martinez, Miami University ; Maria L. Weese, Miami University ; Allison Jones-Farmer, Miami University
 
 
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