IEEE

Accelerating Deep Convolutional Neural Networks Using Number Theoretic Transform

Abstract: Modern deep convolutional neural networks (CNNs) suffer from high computational complexity due to excessive convolution operations. Recently, fast convolution algorithms such as fast Fourier ...
IEEE

Using SHAP Values to Validate Model’s Uncertain Decision for ML-based Lightpath Quality-of-Transmission Estimation

Abstract: We apply Quantile Regression (QR) for lightpath quality-of-transmission (QoT) estimation with the aim of identifying uncertain decisions and then exploit Shapley Additive Explanations (SHAP) ...