2 citations · 4 across the 3 of their papers we have counts for
5 papers
Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Multi-Way Financial Modelling
Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic
Analytics of financial data is inherently a Big Data paradigm, as such data are collected over many assets, asset classes, countries, and time periods. This represents a challenge…
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 Networks for Multi-Modal Non-Euclidean Data
Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic
Modern data sources are typically of large scale and multi-modal natures, and acquired on irregular domains, which poses serious challenges to traditional deep learning models. The…
Multi-Graph Tensor Networks
Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic
The irregular and multi-modal nature of numerous modern data sources poses serious challenges for traditional deep learning algorithms. To this end, recent efforts have generalized…
Supervised Learning for Non-Sequential Data: A Canonical Polyadic Decomposition Approach
Alexandros Haliassos, Kriton Konstantinidis, Danilo P. Mandic
Efficient modelling of feature interactions underpins supervised learning for non-sequential tasks, characterized by a lack of inherent ordering of features (variables). The brute…