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Found 4 papers, 3 papers with code
PCNN: Pattern-based Fine-Grained Regular Pruning towards Optimizing CNN Accelerators
Weight pruning is a powerful technique to realize model compression.
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Existing domain adaptation methods aim at learning features that can be generalized among domains.
Ranked #3 on
Domain Adaptation
on USPS-to-MNIST
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models
Remarkable achievements have been attained by deep neural networks in various applications.
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
Different from traditional knowledge distillation - a knowledge transformation methodology among networks, which forces student neural networks to approximate the softmax layer outputs of pre-trained teacher neural networks, the proposed self distillation framework distills knowledge within network itself.
