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Found 2 papers, 1 papers with code
Unsupervised Learning under Latent Label Shift
Thus motivated, we introduce a practical algorithm that leverages domain-discriminative models as follows: (i) push examples through domain discriminator $p(d|\mathbf{x})$; (ii) discretize the data by clustering examples in $p(d|\mathbf{x})$ space; (iii) perform non-negative matrix factorization on the discrete data; (iv) combine the recovered $p(y|d)$ with the discriminator outputs $p(d|\mathbf{x})$ to compute $p_d(y|x) \; \forall d$.
Ant Colony Inspired Machine Learning Algorithm for Identifying and Emulating Virtual Sensors
In order to identify the subset of sensors whose readings can be emulated, the sensors must be grouped into clusters.
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