INFINITE-DIMENSIONAL GRADIENT-BASED DESCENT FOR ALPHA-DIVERGENCE MINIMISATION

This paper introduces the (α, Γ)-descent, an iterative algorithm which operates on measures and performs α-divergence minimisation in a Bayesian framework. This gradient-based procedure extends the commonly-used variational approximation by adding a prior on the variational parameters in the form of...

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Veröffentlicht in:	The Annals of statistics 2021-08, Vol.49 (4), p.2250-2270
Hauptverfasser:	Daudel, Kamélia, Douc, Randal, Portier, François
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Cognitive tasks Divergence Iterative algorithms Iterative methods Machine learning Mathematics Optimization Parameters Probabilistic models Statistics Studies
Online-Zugang:	Volltext
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