Search Results for author:
Found 1 papers, 0 papers with code
Neural Networks with (Low-Precision) Polynomial Approximations: New Insights and Techniques for Accuracy Improvement
Experiments showed that combination of our solutions is very effective: at the same precision, our PANN is 10% to 50% more accurate than state-of-the-arts; and at the same accuracy, our PANN only requires a precision of $2^{-9}$ while state-of-the-art solution requires a precision of $2^{-12}$ using the ResNet-20 model on CIFAR-10 dataset.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
