74 citations · 166 across the 10 of their papers we have counts for
9 papers
Active information, missing data and prevalence estimation
Ola Hössjer, Daniel Andrés Díaz-Pachón, Chen Zhao +1
The topic of this paper is prevalence estimation from the perspective of active information. Prevalence among tested individuals has an upward bias under the assumption that indivi…
High Dimensional Mode Hunting Using Pettiest Components Analysis
Tianhao Liu, Daniel Andrés Díaz-Pachón, J. Sunil Rao +1
Principal components analysis has been used to reduce the dimensionality of datasets for a long time. In this paper, we will demonstrate that in mode detection the components of sm…
Hypothesis testing with active information
Daniel Andrés Díaz-Pachón, Juan Pablo Sáenz, J. Sunil Rao
We develop hypothesis testing for active information -the averaged quantity in the Kullback-Liebler divergence. To our knowledge, this is the first paper to derive exact probabilit…
Prediction Weighted Maximum Frequency Selection
Hongmei Liu, J. Sunil Rao
Shrinkage estimators that possess the ability to produce sparse solutions have become increasingly important to the analysis of today's complex datasets. Examples include the LASSO…
Precision Therapeutic Biomarker Identification with Application to the Cancer Genome Project
Hongmei Liu, J. Sunil Rao
Cancer cell lines have frequently been used to link drug sensitivity and resistance with genomic profiles. To capture genomic complexity in cancer, the Cancer Genome Project (CGP)…
Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods
Jean-Eudes Dazard, Michael Choe, Michael LeBlanc +1
We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling…