13 citations · 25 across the 7 of their papers we have counts for
4 papers · 1 filter
Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching
Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia +2
Supervised contrastive loss (SCL) is a competitive and often superior alternative to the cross-entropy loss for classification. While prior studies have demonstrated that both loss…
On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data
Tina Behnia, Ganesh Ramachandra Kini, Vala Vakilian +1
Various logit-adjusted parameterizations of the cross-entropy (CE) loss have been proposed as alternatives to weighted CE for training large models on label-imbalanced data far bey…
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Christos Thrampoulidis, Ganesh R. Kini, Vala Vakilian +1
Neural Collapse refers to the remarkable structural properties characterizing the geometry of class embeddings and classifier weights, found by deep nets when trained beyond zero t…
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini, Orestis Paraskevas, Samet Oymak +1
The goal in label-imbalanced and group-sensitive classification is to optimize relevant metrics such as balanced error and equal opportunity. Classical methods, such as weighted cr…