Regression has primarily been attempted through support vector regression (Kim et al., 2006;Zhang and Varadarajan, 2006;Yang et al., 2015).
probabilistic matrix factorization (Tang et al., 2013), linear regression (Lu et al., 2010), and extended tensor factorization models (Moghaddam et al., 2012) have successfully been used to integrate sophisticated constraints into the learning process and have achieved improvements over regular regression models.