21 citations · 26 across the 8 of their papers we have counts for
8 papers
HOTTBOX: Higher Order Tensor ToolBOX
Ilya Kisil, Giuseppe G. Calvi, Bruno S. Dees +1
HOTTBOX is a Python library for exploratory analysis and visualisation of multi-dimensional arrays of data, also known as tensors. The library includes methods ranging from standar…
Reducing Computational Complexity of Tensor Contractions via Tensor-Train Networks
Ilya Kisil, Giuseppe G. Calvi, Kriton Konstantinidis +2
There is a significant expansion in both volume and range of applications along with the concomitant increase in the variety of data sources. These ever-expanding trends have highl…
Tensor-Train Recurrent Neural Networks for Interpretable Multi-Way Financial Forecasting
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. However, when dealing wit…
Tight Lower Bound on the Tensor Rank based on the Maximally Square Unfolding
Giuseppe G. Calvi, Bruno Scalzo Dees, Danilo P. Mandic
Tensors decompositions are a class of tools for analysing datasets of high dimensionality and variety in a natural manner, with the Canonical Polyadic Decomposition (CPD) being a m…
Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer: From First Principles to Tensor Valued Back-Propagation
Giuseppe G. Calvi, Ahmad Moniri, Mahmoud Mahfouz +2
This work aims to help resolve the two main stumbling blocks in the application of Deep Neural Networks (DNNs), that is, the exceedingly large number of trainable parameters and th…
Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition
Anh-Huy Phan, Andrzej Cichocki, Ivan Oseledets +3
The Canonical Polyadic decomposition (CPD) is a convenient and intuitive tool for tensor factorization; however, for higher-order tensors, it often exhibits high computational cost…
The sum of tensor networks
Giuseppe G. Calvi, Ilia Kisil, Danilo P. Mandic
Tensor networks (TNs) have been gaining interest as multiway data analysis tools owing to their ability to tackle the curse of dimensionality and to represent tensors as smaller-sc…
Tensor Valued Common and Individual Feature Extraction: Multi-dimensional Perspective
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…