Legend:
CC = Baltimore Convention Center,
H = Hilton Baltimore
* = applied session ! = JSM meeting theme
460 *
Wed, 8/2/2017,
8:30 AM -
10:20 AM
CC-322
Clustering Methods for Big Data Problems — Topic Contributed Papers
Section on Statistical Learning and Data Science
Organizer(s): Ranjan Maitra, Iowa State University
Chair(s): Wei-Chen Chen, FDA/CDRH
8:35 AM
A Parallel EM Algorithm for Statistical Learning via Mixture Models
—
Geoffrey McLachlan, The University of Queensland
8:55 AM
Clustering Errored Sequence Reads to Estimate Unique Amplicons and Abundance
—
Karin Dorman, Iowa State University ; Xiyu Peng, Iowa State University
9:15 AM
A Bayesian Lasso Functional Clustering Model
—
Alejandro Murua, Universite de Montreal ; Folly Adjogou, Université de Montréal ; Wolfgang Raffelsberger, Institut de Génetique et de Biologie Moléculaire et Cellulaire, Université de Strasbourg
9:35 AM
Hierarchical Latent Factor Models for Improving the Prediction of Surgical Complications Across Hospitals
—
Elizabeth Lorenzi, Duke University ; Katherine Heller, Duke University ; Ricardo Henao, Duke University ; Zhifei Sun, Duke University
9:55 AM
Efficient Parallelized K-Means for Clustering Big Data
—
Geoffrey Thompson, Iowa State University ; Ranjan Maitra, Iowa State University
10:15 AM
Floor Discussion