2291d2ec3b3048d1a6f86c2c4591b7e0-Reviews.html

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The goal of this work is to automatically discover latent domains in a training set, which is subsequently used in a domain adaptation framework to yield improved classification performance on a test set. The paper defines a function that measures the difference between two feature vectors over a specified kernel. The goal is to partition the data points into domains such that the function is maximized over the set of points across each pair of domains. The problem is formulated as an integer programming problem with two constraints: each point is assigned to exactly one domain and the distribution over class labels in each domain must match the input distribution over the entire point set.