1 code implementation • 6 Jul 2022 • Dexiong Chen, Bowen Fan, Carlos Oliver, Karsten Borgwardt
Our approach integrates Multidimensional Scaling (MDS) and Wasserstein Procrustes analysis into a joint optimization problem to simultaneously generate isometric embeddings of data and learn correspondences between instances from two different datasets, while only requiring intra-dataset pairwise dissimilarities as input.