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COLT
2006
Springer

Unifying Divergence Minimization and Statistical Inference Via Convex Duality

11 years 3 months ago
Unifying Divergence Minimization and Statistical Inference Via Convex Duality
Abstract. In this paper we unify divergence minimization and statistical inference by means of convex duality. In the process of doing so, we prove that the dual of approximate maximum entropy estimation is maximum a posteriori estimation. Moreover, our treatment leads to stability and convergence bounds for many statistical learning problems. Finally, we show how an algorithm by Zhang can be used to solve this class of optimization problems efficiently.
Yasemin Altun, Alexander J. Smola
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where COLT
Authors Yasemin Altun, Alexander J. Smola
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