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Found 2 papers, 2 papers with code
Semi-Supervised Clustering via Information-Theoretic Markov Chain Aggregation
The introduced Constrained Markov Clustering (CoMaC) is an extension of a recent information-theoretic framework for (unsupervised) Markov aggregation to the semi-supervised case.
Processing of missing data by neural networks
We propose a general, theoretically justified mechanism for processing missing data by neural networks.
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