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cs.LG2025
Towards Scalable Backpropagation-Free Gradient Estimation
Daniel Wang, Evan Markou, Dylan Campbell
While backpropagation--reverse-mode automatic differentiation--has been extraordinarily successful in deep learning, it requires two passes (forward and backward) through the neura…
cs.LG2024
Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame
Evan Markou, Thalaiyasingam Ajanthan, Stephen Gould
Neural Collapse (NC) is a recently observed phenomenon in neural networks that characterises the solution space of the final classifier layer when trained until zero training loss.…