Channel pruning is used to reduce the number of weights in a Convolution...
Convolutional neural networks (CNNs) have dramatically improved the accu...
Artificial Intelligence (AI) is becoming more pervasive through all leve...
Convolutional neural networks (CNNs) are used in many embedded applicati...
The computation and memory needed for Convolutional Neural Network (CNN)...
Hardware-Software Co-Design is a highly successful strategy for improvin...
Convolutional neural networks (CNNs) are widely used for classification
...
We present a user study to investigate the impact of explanations on
non...
Quantization of weights and activations in Deep Neural Networks (DNNs) i...
Modern deep neural networks (DNNs) spend a large amount of their executi...
Modern deep neural networks (DNNs) spend a large amount of their executi...
Assessing and understanding intelligent agents is a difficult task for u...
How should an AI-based explanation system explain an agent's complex beh...
Deep Neural Networks (DNNs) require very large amounts of computation bo...
Deep neural networks (DNNs) require very large amounts of computation bo...
Convolutional neural networks (CNNs) have emerged as one of the most
suc...
We propose a scheme for reduced-precision representation of floating poi...