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Epanechnikov Variational Autoencoder
In this paper, we bridge Variational Autoencoders (VAEs) [17] and kernel density estimations (KDEs) [25 ],[23] by approximating the posterior by KDEs and deriving an upper bound of the Kullback-Leibler (KL) divergence in the evidence lower bound (ELBO).
Riemann-Lebesgue Forest for Regression
We propose a novel ensemble method called Riemann-Lebesgue Forest (RLF) for regression.
On Subagging Boosted Probit Model Trees
With the insight of variance-bias decomposition, we design a new hybrid bagging-boosting algorithm named SBPMT for classification problems.
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