2026
Robust Training of Neural Networks at Arbitrary Precision and Sparsity
ICLR 2026poster
The discontinuous operations inherent in quantization and sparsification introduce a long-standing obstacle to backpropagation, particularly in ultra-low precision and sparse regimes. While the community has long viewed quantization as unfriendly to gradient descent due to its lack of smoothness, we…