SupplementaryMaterialFor StochasticMultipleTargetSamplingGradientDescent

By contrast, there isonly one quadratic programming problem solving inour proposed method, which significantly reduces time complexity, especially when the number of particles is high. The mean square error for each task and the average results are shown in Table 1. MT-SGD outperforms thesecond-best method, MOO-SVGD, with0.2251vs. However, on the one hand, computingU's entries can be accelerated in practice bycalculating theminparallel sincethereisnointeraction between themduring forwardpass. Allimagesareresizedto 64 64 3. Due tospace constraints, we report only the abbreviation ofeach task inthe main paper,their full namesarepresentedbelow.