Embedding Compression with Isotropic Iterative Quantization
Table 3: Categorization Results.
['[EMPTY]', '[BOLD] Method', '[BOLD] AP', '[BOLD] BLESS', '[BOLD] Battig', '[BOLD] ESSLI']
One sees that the proposed IIQ method works better than ITQ, DCCL, and the pruning method on all data sets. But NLB sometimes achieves the best result for example on Battig. For ESSLI, IIQ even outperforms the original GloVe and HDC embedding.