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Keyword Search Criteria: feature selection returned 11 record(s)
Sunday, 07/30/2017
Detecting Local Sparsity and High-Order Interactions with Iterative Random Forests
Sumanta Basu, Cornell University; James Bentley Brown, Lawrence Berkeley National Laboratory; Bin Yu, University of California, Berkeley
4:55 PM

Monday, 07/31/2017
Impact of Missing Data in Feature Selection
Carmen Khoo


A Bayesian Mixture Model for Clustering and Selection of Feature Occurrence Rates Under Mean Constraints
Qiwei Li, Rice University; Michele Guindani, University of California, Irvine; Brian Reich, NCSU; Howard Bondell, NC State University; Marina Vannucci, Rice University


A Bayesian Mixture Model for Clustering and Selection of Feature Occurrence Rates Under Mean Constraints
Qiwei Li, Rice University; Michele Guindani, University of California, Irvine; Brian Reich, NCSU; Howard Bondell, NC State University; Marina Vannucci, Rice University
9:15 AM

An Integrative Model for Assessing Multimodal Neuroimaging Signatures of Post-Traumatic Stress Disorder
Fengqing Zhang, Drexel University; Xin Niu, Drexel University
11:55 AM

Tuesday, 08/01/2017
A Bayesian Model for Integrating High-Throughput Multi-Omics Data with Missingness Handling
Zhou Fang, Department of Biostatistics, University of Pittsburgh; Tianzhou Ma, Department of Biostatistics, University of Pittsburgh; Li Zhu, University of Pittsburgh; George Tseng, University of Pittsburgh; Qi Yan, Division of Pulmonary Medicine, Allergy and Immunology, Children's Hospital of Pittsburgh ; Wei Chen, University of Pittsburgh


Robust Feature Selection and Cell Line Classification with Electric Cell-Substrate Impedance Sensing Data
Megan Gelsinger, Cornell University; David S Matteson, Cornell University; Laurie Tupper, Williams College


Robust Feature Selection and Cell Line Classification with Electric Cell-Substrate Impedance Sensing Data
Megan Gelsinger, Cornell University; David S Matteson, Cornell University; Laurie Tupper, Williams College
8:50 AM

Wednesday, 08/02/2017
Exploring High-Dimensional Feature Selection Using Reproducibility Methodology
Frank Shen, Penn State University


Exploring High-Dimensional Feature Selection Using Reproducibility Methodology
Frank Shen, Penn State University
9:15 AM

Rare Feature Selection in High Dimensions
Xiaohan Yan, Cornell University; Jacob Bien, Cornell University
10:35 AM

 
 
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