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Compressive Classification (Machine Learning without learning)

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Schellekens, Vincent [UCL] Jacques, Laurent [UCL]

Compressive learning is a framework where (so far unsupervised) learning tasks use not the entire dataset but a compressed summary (sketch) of it. We propose a compressive learning classification method, and a novel sketch function for images.

Document type Communication à un colloque (Conference Paper) – Présentation orale avec comité de sélection
Access type Accès libre
Publication date 2018
Language Anglais
Conference "iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques", Marseille, France (du 21/11/2018 au 23/11/2018)
Journal information "ITWIST'18" - no. 8 (2018)
Peer reviewed yes
Publisher iTWIST'18
Publication status Publié
Affiliations UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique
UCL - SST/ICTM/INMA - Pôle en ingénierie mathématique
Keywords Compressive Learning ; Sketched Learning ; Random Neural Network
Links
Bibliographic reference Schellekens, Vincent ; Jacques, Laurent. Compressive Classification (Machine Learning without learning).iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques (Marseille, France, du 21/11/2018 au 23/11/2018). In: ITWIST'18, no. 8 (2018)
Permanent URL http://hdl.handle.net/2078.1/209861