Robust 'Huber mean' for geometric data protects against noise and outliers

In an era driven by complex data, scientists are increasingly encountering information that doesn't lie neatly on flat, ...
IEEE

Deep-Learning-Aided Alternating Least Squares for Tensor CP Decomposition and Its Application to Massive MIMO Channel Estimation

Abstract: CANDECOMP/PARAFAC (CP) decomposition is the mostly used model to formulate the received tensor signal in a massive MIMO system, as the receiver generally sums the components from different ...
IEEE

Deep Co-Training Partial Least Squares Model for Semi-Supervised Industrial Soft Sensing

Abstract: Data-driven soft sensing has become quite popular in recent years, which can provide real-time estimations of key variables in industrial processes. While the introduction of deep learning ...