FFR adapts Forward-Forward learning to regression via ordinal competitive goodness, stratified ladder layers, and hierarchical uncertainty-aware prediction, recovering 98.6% of backpropagation accuracy with substantially lower peak memory.
Function regression using the forward forward training and inferring paradigm.arXiv preprint arXiv:2510.06762, 2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
FFR: Forward-Forward Learning for Regression
FFR adapts Forward-Forward learning to regression via ordinal competitive goodness, stratified ladder layers, and hierarchical uncertainty-aware prediction, recovering 98.6% of backpropagation accuracy with substantially lower peak memory.