research
∙
12/23/2022
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse
With the ever-growing model size and the limited availability of labeled...
share
research
∙
10/04/2022
Are All Losses Created Equal: A Neural Collapse Perspective
While cross entropy (CE) is the most commonly used loss to train deep ne...
research
∙
09/21/2022
A Validation Approach to Over-parameterized Matrix and Image Recovery
In this paper, we study the problem of recovering a low-rank matrix from...
research
∙
03/02/2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
When training deep neural networks for classification tasks, an intrigui...
research
∙
05/06/2021