PhD student, Stanford University
3 papers at NeurIPS 2025
We propose a principled error broadcasting framework to serve as a more biologically realistic and flexible alternative to the backpropagation algorithm, based on the orthogonality property of nonlinear MMSE estimators.
We propose to replace self-attention layers with linear estimators through the derived CCA error bound, achieving inference speedups with favorable accuracy trade-off.
