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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| 格式: | 文件 |
| 语言: | English |
| 出版: |
Society for Industrial and Applied Mathematics
2021
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| 在线阅读: | https://hdl.handle.net/1721.1/137446 |