Coupled tensor decomposition: A step towards robust components
Combining information present in multiple datasets is one of the key challenges to fully benefit from the increasing availability of data in a variety of fields. Coupled tensor factorization aims to address this challenge by performing a simultaneous decomposition of different tensors. However, tens...
| Main Authors: | , , , |
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| Format: | Conference item |
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Institute of Electrical and Electronics Engineers
2016
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| _version_ | 1826261721968279552 |
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| author | Genicot, M Absil, P Lambiotte, R Sami, S |
| author_facet | Genicot, M Absil, P Lambiotte, R Sami, S |
| author_sort | Genicot, M |
| collection | OXFORD |
| description | Combining information present in multiple datasets is one of the key challenges to fully benefit from the increasing availability of data in a variety of fields. Coupled tensor factorization aims to address this challenge by performing a simultaneous decomposition of different tensors. However, tensor factorization tends to suffer from a lack of robustness as the number of components affects the results to a large extent. In this work, a general framework for coupled tensor factorization is built to extract reliable components. Results from both individual and coupled decompositions are compared and divergence measures are used to adapt the number of components. It results in a joint decomposition method with (i) a variable number of components, (ii) shared and unshared components among tensors and (iii) robust components. Results on simulated data show a better modelling of the sources composing the datasets and an improved evaluation of the number of shared sources. |
| first_indexed | 2024-03-06T19:25:37Z |
| format | Conference item |
| id | oxford-uuid:1b9883dd-2126-4a92-b743-72e91b6542ca |
| institution | University of Oxford |
| last_indexed | 2024-03-06T19:25:37Z |
| publishDate | 2016 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | oxford-uuid:1b9883dd-2126-4a92-b743-72e91b6542ca2022-03-26T11:01:15ZCoupled tensor decomposition: A step towards robust componentsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:1b9883dd-2126-4a92-b743-72e91b6542caSymplectic Elements at OxfordInstitute of Electrical and Electronics Engineers2016Genicot, MAbsil, PLambiotte, RSami, SCombining information present in multiple datasets is one of the key challenges to fully benefit from the increasing availability of data in a variety of fields. Coupled tensor factorization aims to address this challenge by performing a simultaneous decomposition of different tensors. However, tensor factorization tends to suffer from a lack of robustness as the number of components affects the results to a large extent. In this work, a general framework for coupled tensor factorization is built to extract reliable components. Results from both individual and coupled decompositions are compared and divergence measures are used to adapt the number of components. It results in a joint decomposition method with (i) a variable number of components, (ii) shared and unshared components among tensors and (iii) robust components. Results on simulated data show a better modelling of the sources composing the datasets and an improved evaluation of the number of shared sources. |
| spellingShingle | Genicot, M Absil, P Lambiotte, R Sami, S Coupled tensor decomposition: A step towards robust components |
| title | Coupled tensor decomposition: A step towards robust components |
| title_full | Coupled tensor decomposition: A step towards robust components |
| title_fullStr | Coupled tensor decomposition: A step towards robust components |
| title_full_unstemmed | Coupled tensor decomposition: A step towards robust components |
| title_short | Coupled tensor decomposition: A step towards robust components |
| title_sort | coupled tensor decomposition a step towards robust components |
| work_keys_str_mv | AT genicotm coupledtensordecompositionasteptowardsrobustcomponents AT absilp coupledtensordecompositionasteptowardsrobustcomponents AT lambiotter coupledtensordecompositionasteptowardsrobustcomponents AT samis coupledtensordecompositionasteptowardsrobustcomponents |