FADE adapts per-parameter weight decay rates online via approximate meta-gradient descent to improve controlled forgetting over fixed decay in online tracking and streaming classification.
Loss of plasticity in deep continual learning
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
NORACL grows neurons only when saturation signals fire, matching or beating static continual-learning models that know the future task budget while using fewer parameters.
A survey compiling RL methods, challenges, data resources, and applications for enhancing reasoning in large language models and large reasoning models since DeepSeek-R1.
citing papers explorer
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Learning to Forget: Continual Learning with Adaptive Weight Decay
FADE adapts per-parameter weight decay rates online via approximate meta-gradient descent to improve controlled forgetting over fixed decay in online tracking and streaming classification.
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NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning
NORACL grows neurons only when saturation signals fire, matching or beating static continual-learning models that know the future task budget while using fewer parameters.
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A Survey of Reinforcement Learning for Large Reasoning Models
A survey compiling RL methods, challenges, data resources, and applications for enhancing reasoning in large language models and large reasoning models since DeepSeek-R1.