2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 2 cited
Exploiting Weight Redundancy in CNNs: Beyond Pruning and Quantization
Yuan Wen, David Gregg
Pruning and quantization are proven methods for improving the performance and storage efficiency of convolutional neural networks (CNNs). Pruning removes near-zero weights in tenso…
cs.LG2020★ 1 cited
TASO: Time and Space Optimization for Memory-Constrained DNN Inference
Yuan Wen, Andrew Anderson, Valentin Radu +2
Convolutional neural networks (CNNs) are used in many embedded applications, from industrial robotics and automation systems to biometric identification on mobile devices. State-of…
cs.LG2020
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs
Valentin Radu, Kuba Kaszyk, Yuan Wen +6
Convolutional Neural Networks (CNN) are becoming a common presence in many applications and services, due to their superior recognition accuracy. They are increasingly being used o…