The expectation-maximization (EM) algorithm is a cornerstone technique for parameter estimation in statistical models that incorporate latent variables or incomplete data. By iteratively alternating ...

The least absolute shrinkage and selection operator (Lasso) estimation of regression coefficients can be expressed as Bayesian posterior mode estimation of the regression coefficients under various ...

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...