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Gradient-EMBayesianMeta-learning
The key idea behind Bayesian meta-learning is empirical Bayes inference of hierarchical model.
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies Hanna Ziesche and Leonel Rozo
Robots often rely on a repertoire of previously-learned motion policies for performing tasks of diverse complexities.
TheGeneralization-StabilityTradeoffInNeural NetworkPruning
This motivation is particularly relevant given the perhaps surprising observation that a wide variety of pruning approaches increase test accuracy despite sometimes massivereductions inparameter counts.
