ReMeDe Trees are hard, axis-aligned decision trees with a learned internal memory, trained by backpropagation through time, achieving perfect accuracy on synthetic delayed-sign and sign-memory tasks.
Learning online smooth predictors for realtime camera planning using recurrent decision trees
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory
ReMeDe Trees are hard, axis-aligned decision trees with a learned internal memory, trained by backpropagation through time, achieving perfect accuracy on synthetic delayed-sign and sign-memory tasks.