High-dimensional statistical modelling addresses situations in which the number of variables (p) rivals or exceeds the number of observations (n). In these settings, classical estimation techniques ...

Modern scientific investigations frequently generate datasets with thousands to millions of features, ranging from genomic profiles to sensor measurements. Analysing such high-dimensional data demands ...

A new variable selection method was proposed recently by a research team from the Institute of Intelligent Machines, Hefei Institutes of Physical Science (HFIPS) of Chinese Academy of Sciences (CAS) ...