BiPer: Binary Neural Networks using a Periodic Function

arXiv:2404.01278v1 Announce Type: new
Abstract: Quantized neural networks employ reduced precision representations for both weights and activations. This quantization process significantly reduces the memory requirements and computational complexity of the network. Binary Neural Networks (BNNs) are the extreme quantization case, representing values with just one bit. Since the sign function is typically used to map real values to binary values, smooth approximations are introduced to mimic the gradients during error backpropagation. Thus, the mismatch between the forward and backward models …

arxiv binary cs.cv function networks neural networks type