Optimization readiness, defined from gradient strength and reliability, lower-bounds one-step optimization gain and outperforms rank-based diagnostics in predicting neural network trainability across continual learning settings.
Mitigating plasticity loss in continual reinforcement learning by reducing churn
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
-
Predicting Plasticity in Deep Continual Learning: A Theoretical Perspective
Optimization readiness, defined from gradient strength and reliability, lower-bounds one-step optimization gain and outperforms rank-based diagnostics in predicting neural network trainability across continual learning settings.