Research map / Image generation / Autoregressive and latent generation
Comparative Deep Learning of Hybrid Representations for Image Recommendations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use comparative triplet training instead of naive user-image doublet training (ablation) | Dual-net hybrid representations · Flickr image recommendation | Precision@K and Recall@K | Helped |
| Use cross-entropy loss instead of hinge loss (ablation) | CDL · Flickr image recommendation | Precision@K and Recall@K | Helped |
| Use CDL instead of SIDL | Image recommendation · Flickr image recommendation | Precision: 42.58% | Helped |
| Use CDL instead of SIDL | Image recommendation · Flickr image recommendation | Recall: 46.50% | Helped |
| Add social information to constrain LMNN | LMNN · Flickr image recommendation | Recommendation performance | Helped |
| Use deep ImageNet features instead of hand-crafted BoW features | Borda Count recommendation · Flickr image recommendation | Recommendation performance | Helped |
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