A novel Empirical Bayes with Reversible Jump Markov Chain in User-Movie Recommendation system

Dey et al. (2017), bayesian formulation of this problem is discussed. Hyper prameter choice was the major issue in that paper. However this problem was attempted only after suitable choice of feature dimension for user and movie feature vector. Usual method used to select such feature dimension is nothing but one dimensional grid search that select the dimension which minimizes the test error. This approach is boring as it attracts extra computational burden to select the feature dimension.