Normalized training loss vs. baselines (Facebook).
<p>DCOR reports both reconstruction-only and total (with RLC); baselines report reconstruction-only. Each curve is normalized as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0335135#pone.0335135.e243" target="_blank">Eq (29)</a> by di...
-д хадгалсан:
| Үндсэн зохиолч: | |
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| Бусад зохиолчид: | , , |
| Хэвлэсэн: |
2025
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| Нөхцлүүд: | |
| Шошгууд: |
Шошго нэмэх
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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| Тойм: | <p>DCOR reports both reconstruction-only and total (with RLC); baselines report reconstruction-only. Each curve is normalized as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0335135#pone.0335135.e243" target="_blank">Eq (29)</a> by dividing by its epoch-1 value and EMA-smoothed (exponential moving average) with , where the EMA is computed as with . This normalization enables fair visual comparison across methods with different objectives and scales; the plot therefore emphasizes relative convergence trends (shape and stability) rather than raw magnitudes. Consistent with DCOR’s design, RLC regularizes late-phase training: the reconstruction curve decreases more conservatively than methods that minimize reconstruction alone, while the total objective continues to decrease.</p> |
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