VQ4ALL builds a single universal codebook from the weight distributions of several networks, then learns per-network assignments to reconstruct low-bit weights while keeping accuracy close to the original models.
Deep neural network com- pression by in-parallel pruning-quantization
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VQ4ALL: Efficient Neural Network Representation via a Universal Codebook
VQ4ALL builds a single universal codebook from the weight distributions of several networks, then learns per-network assignments to reconstruct low-bit weights while keeping accuracy close to the original models.