0ff39bbbf981ac0151d340c9aa40e63e-Reviews.html

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper proposes a matrix completion approach to the cross domain classification task, which is capable of exploiting labeled data in an auxiliary domain and also unlabeled parellel data. The approach involves two steps. First, it constructs a single incomplete matrix that includes all documents and domains, and then completes this matrix while enforcing low-rank and sparsity conditions using the projected gradient descent algorithm. Second, it reduces the feature dimension of this completed matrix using LSI, and then trains a standard classifier on this new representation.