Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching

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.

On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data

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.

Label-Imbalanced and Group-Sensitive Classification under Overparameterization

1 code implementation • NeurIPS 2021 • Ganesh Ramachandra Kini, Orestis Paraskevas, Samet Oymak, Christos Thrampoulidis

The goal in label-imbalanced and group-sensitive classification is to optimize relevant metrics such as balanced error and equal opportunity.

Classification General Classification