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Found 3 papers, 2 papers with code
On generalization in moment-based domain adaptation
Domain adaptation algorithms are designed to minimize the misclassification risk of a discriminative model for a target domain with little training data by adapting a model from a source domain with a large amount of training data.
Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment
A novel approach for unsupervised domain adaptation for neural networks is proposed.
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning
We prove that CMD is a metric on the set of probability distributions on a compact interval.
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