Jinglan Liu

On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks

Compression is a key step to deploy large neural networks on resource-constrained platforms. As a popular compression technique, quantization constrains the number of distinct weight values and thus reducing the number of bits required to represent and store each weight. In this paper, we study the…