gradient-masking

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ishaaqdev / Staged-Embarrassment-Learning

Staged Embarrassment Learning (SEL) is a bio-inspired framework for efficient Deep Learning. Inspired by a child’s rapid correction after a mistake, SEL uses dynamic gradient sparsity to focus compute on high-loss "embarrassing" samples . It achieves up to 99% FLOPs reduction, making it ideal for Edge AI.

computer-vision pytorch resnet cifar10 curriculum-learning edge-ai green-ai sparse-training model-optimization efficient-deep-learning gradient-masking

Updated Apr 23, 2026
Jupyter Notebook

Hinedes / Proteus

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Code for "Matryoshka Plasticity: Exploiting Nested Transformer Structure for Zero‑Overhead Continual Learning"

machine-learning deep-learning edge-computing continual-learning catastrophic-forgetting edge-ai pretraining llm matformer nested-transformers gradient-masking

Updated May 3, 2026
Python

ishaaqdev / Staged-Embarrassment-Learning-SEL

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The most compute-efficient training framework for ResNet architectures. 99.1% FLOPs reduction. 100% Local.

computer-vision pytorch resnet cifar10 curriculum-learning edge-ai green-ai sparse-training model-optimization efficient-deep-learning gradient-masking

Updated May 28, 2026
Jupyter Notebook

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