An Empirical Study of Self-Supervised Learning with Wasserstein Distance
In this study, we consider the problem of self-supervised learning (SSL) utilizing the 1-Wasserstein distance on a tree structure (a.k.a., Tree-Wasserstein distance (TWD)), where TWD is defined as the L1 distance between two tree-embedded vectors. In SSL methods, the cosine similarity is often utili...
Kaydedildi:
| Asıl Yazarlar: | , , , , , , |
|---|---|
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
MDPI AG
2024-10-01
|
| Seri Bilgileri: | Entropy |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/1099-4300/26/11/939 |
| Etiketler: |
Etiket eklenmemiş, İlk siz ekleyin!
|