3 citations · 5 across the 4 of their papers we have counts for
4 papers
A MAC-less Neural Inference Processor Supporting Compressed, Variable Precision Weights
Vincenzo Liguori
This paper introduces two architectures for the inference of convolutional neural networks (CNNs). Both architectures exploit weight sparsity and compression to reduce computationa…
Pyramid Vector Quantization and Bit Level Sparsity in Weights for Efficient Neural Networks Inference
Vincenzo Liguori
This paper discusses three basic blocks for the inference of convolutional neural networks (CNNs). Pyramid Vector Quantization (PVQ) is discussed as an effective quantizer for CNNs…
Pyramid Vector Quantization for Deep Learning
Vincenzo Liguori
This paper explores the use of Pyramid Vector Quantization (PVQ) to reduce the computational cost for a variety of neural networks (NNs) while, at the same time, compressing the we…
Vector Quantization for Machine Vision
Vincenzo Liguori
This paper shows how to reduce the computational cost for a variety of common machine vision tasks by operating directly in the compressed domain, particularly in the context of ha…