Gentili colleghi,

domani, mercoledi' 7 settembre, alle ore 15 presso la sede di Milano dell'IMATI, via Corti 12 - sala A,

Chaitanya Joshi, dall'Universita' di Waikato (Hamilton, Nuova Zelanda) terra' il seminario:

Improving grid based Bayesian inference

Abstract:
In some cases, computational benefit can be gained by exploring the hyper
parameter space using a deterministic set of grid points instead of a
Markov chain. We view this as a numerical integration problem and make
three unique contributions. First, we explore the space using low
discrepancy point sets instead of a grid. This allows for accurate
estimation of marginals of any shape at a much lower computational cost
than a grid based approach and thus makes it possible to extend the
computational benefit to a hyper parameter space with higher dimensionality
(10 or more). Second, we propose a new, quick and easy method to estimate
the marginal using a least squares polynomial and prove the conditions
under which this polynomial will converge to the true marginal. Our results
are valid for a wide range of point sets including grids, random points and
low discrepancy points. Third, we show that further accuracy and efficiency
can be gained by taking into consideration the functional decomposition of
the integrand and illustrate how this can be done using anchored f-ANOVA on
weighted spaces.

-- 
Dott. Antonella Bodini 					
CNR-Istituto di Matematica Applicata e Tecnologie Informatiche					
Via Bassini 15, 20133 Milano (Italy)
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