Tensor-based data similarity - Tensor-based study of data similarity
From 01-01-2014 to 31-12-2017
Description
Higher-order tensors are the natural generalizations of vectors (first order) and matrices (second order). Blind signal separation consists of the estimation of signals that are observed in mixed form. Blind system identification is the identification of a dynamical system from output observations only. Tensor decompositions have properties that make them proper tools for these generic problems.In this project we make the step from techniques that rely on the decomposition of a single tensor, to the assessment of data similarity, involving two tensors. We work out a technique that allows us to assess whether two tensors have the same components (in different proportions),while avoiding the explicit computation of the latter. Classical linear algebra does not allow such an analysis. We investigate whether complex data may be associated with the behavior of similar dynamical systems, without explicitly identifying the latter. We develop variants for large-scale sparse data. In particular, we develop tensor tools for analyzing and comparing graphs and networks. We develop a comprehensive framework for mapping data to higher-order tensors, facilitating the use of tensor tools in the case of conventional matrix data. We give a proof of concept for electroencephalographic data analysis, where our technique allows us to compare brain states, and magnetic spectroscopy imaging, where sparse versions allow us to compare the composition of samples.
Team
- Johan Suykens, Co-promoter
- Lieven De Lathauwer, Promoter
Financing
Funding: FWO - Research Foundation - Flanders
Program/Grant Type: FWO Research Grant - FWO Research Grant
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.