Binarized Neural Network
A neural network that constrains weights and activations to ±1, replacing multiply-accumulate operations in the forward pass with XNOR and popcount, greatly reducing computation and storage overhead; it is an extreme form of embedding Boolean circuits.
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Binary neural networks (BNNs) constrain both weights and activations to ±1, so the multiply-accumulate operations in forward propagation can be simplified to XNOR and popcount, greatly reducing computation and storage overhead.
Binarization brings significant accuracy loss and unstable training, so it is often combined with knowledge distillation and multi-stage training.
All Facts (2)
Binary neural networks (BNNs) constrain both weights and activations to ±1, so the multiply-accumulate operations in forward propagation can be simplified to XNOR and popcount, greatly reducing computation and storage overhead.
50%UnverifiedBinarization brings significant accuracy loss and unstable training, so it is often combined with knowledge distillation and multi-stage training.
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