We therefore propose to learn many local linear projections which are individually trained for each unlabeled source phrase.
for each unlabeled source phrase f , we learn a mapping W f ∈ R d×d based on the translations of m of f 's labeled neighbors: Compared to the global projection, we require an additional k-NN query to find the labeled neighbors for each unlabeled source phrase.