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Alpha-Beta Divergence For Variational Inference
[article]
2018
arXiv
pre-print
This paper introduces a variational approximation framework using direct optimization of what is known as the scale invariant Alpha-Beta divergence (sAB divergence). This new objective encompasses most variational objectives that use the Kullback-Leibler, the Rényi or the gamma divergences. It also gives access to objective functions never exploited before in the context of variational inference. This is achieved via two easy to interpret control parameters, which allow for a smooth
arXiv:1805.01045v2
fatcat:ss7gw6fsxjfw3ebom6okysv6a4