__Abstract__
Advances in research technologies over the past few decades have encouraged the proliferation
of massive datasets, revolutionizing statistical perspectives on high-dimensionality. Highthroughput
technologies have become pervasive in diverse scientific disciplines and continued
to generate data of increasingly complex phenomena, altering the course of statistical developments
both in methodology and theory. A major focus of the intensive methodological research
has centered around variable selection, which has become fundamental to knowledge
extraction from such challenging data.
The problem of variable selection refers to the statistical endeavor of selecting a subset of
observed characteristics, which collectively provide a good description of an observed phenomenon.
Of particular interest are settings where such a subset is parsimonious
