To reduce the additional computational cost of the retraining, and to improve the 'usability' of embedding vectors, we propose a framework for incrementally determining embeddings one dimension at a time from 1 to D. As a result, our method always offers the relation that 'any D -right-truncated em-bedding vector is the solution for D -dimensional embeddings of our method'.
in actual use, we only need to construct a relatively higherdimensional embedding vector 'just once', i.e., D = 1000, and then truncate it to an appropriate dimension for the application.