no code implementations • 2 Oct 2023 • Jaidev Gill, Vala Vakilian, Christos Thrampoulidis
Supervised-contrastive loss (SCL) is an alternative to cross-entropy (CE) for classification tasks that makes use of similarities in the embedding space to allow for richer representations.
no code implementations • 13 Jun 2023 • Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia, Jaidev Gill, Christos Thrampoulidis
Supervised contrastive loss (SCL) is a competitive and often superior alternative to the cross-entropy loss for classification.
1 code implementation • 14 Mar 2023 • Tina Behnia, Ganesh Ramachandra Kini, Vala Vakilian, Christos Thrampoulidis
Aiming to extend this theory to non-linear models, we investigate the implicit geometry of classifiers and embeddings that are learned by different CE parameterizations.
no code implementations • 10 Aug 2022 • Christos Thrampoulidis, Ganesh R. Kini, Vala Vakilian, Tina Behnia
However, we caution that convergence worsens with increasing imbalances.
