Compressive Classification (Machine Learning without learning)
(2018) iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques — Location: Marseille, France (21.November.2018)
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- Authors
- Abstract
- 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.
- Affiliations
Citations
Schellekens, V., & Jacques, L. (2018). Compressive Classification (Machine Learning without learning). ITWIST′18, 8. https://hdl.handle.net/2078.5/253543 (Original work published 2018)