A Statistical Learning Theory Framework for Supervised Pattern Discovery
Copyright © SIAM. This paper formalizes a latent variable inference problem we call supervised, pattern discovery, the goal of which is to find sets of observations that belong to a single "pattern." We discuss two versions of the problem and prove uniform risk bounds for both. In the firs...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Society for Industrial and Applied Mathematics
2022
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| Online Access: | https://hdl.handle.net/1721.1/137446.2 |