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Transferable Deep Metric Learning for Clustering
Clustering in high dimension spaces is a difficult task; the usual distance metrics may no longer be appropriate under the curse of dimensionality.
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies
We further show that the different policies we sample present different risk profiles, corresponding to interesting practical applications in interpretability, and represents a first step towards learning the distribution of optimal policies itself.
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