no code implementations • 11 May 2021 • Yao Lei Xu, Giuseppe G. Calvi, Danilo P. Mandic
Recurrent Neural Networks (RNNs) represent the de facto standard machine learning tool for sequence modelling, owing to their expressive power and memory.
no code implementations • 14 Mar 2019 • Giuseppe G. Calvi, Ahmad Moniri, Mahmoud Mahfouz, Qibin Zhao, Danilo P. Mandic
This is achieved through a tensor valued approach, based on the proposed Tucker Tensor Layer (TTL), as an alternative to the dense weight-matrices of DNNs.
no code implementations • 1 Nov 2017 • Ilia Kisil, Giuseppe G. Calvi, Danilo P. Mandic
A novel method for common and individual feature analysis from exceedingly large-scale data is proposed, in order to ensure the tractability of both the computation and storage and thus mitigate the curse of dimensionality, a major bottleneck in modern data science.