Theoretically,Falconn++ asymptotically achieves lower query time complexity than Falconn, an optimal locality-sensitive hashing scheme on angular distance.

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In this section, we present some additional experiments. Empirical setup Most of the experimental setups are the same as those in Section 6, except that now we use 5 parties instead of 3 parties. There are 90 dimensions for a single data in YearPredictionMSD dataset, and we let each party hold 18 dimensions. Empirical results We plot the training loss instead of the testing loss since we are comparing differentobjectivefunctions. A.4 Experimentsonotherdatasets In this section, we present the experiment results on another dataset.