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Artificial Intelligence Paper PDF

19 Pages·2019·English
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by ['Harita']| 2019| 19 pages| English

About Artificial Intelligence Paper

This document summarizes a research paper about providing theoretical guarantees for the convergence of adaptive Bayesian quadrature (ABQ) methods. ABQ methods sequentially select integration points to adapt to the target function, leading to better empirical performance than standard Bayesian quadrature or Monte Carlo integration. However, there were no theoretical guarantees of their convergence. The paper introduces the concept of "weak adaptivity" and proves that ABQ methods that satisfy this property are consistent, identifying a flexible class of adaptive rules that are guaranteed to converge. Weak adaptivity for ABQ is analogous to concepts like detailed balance and ergodicity that guarantee the consistency of Markov chain Monte Carlo methods.

Detailed Information

Author:['Harita']
Publication Year:2019
Pages:19
Language:English
Format:PDF
Price:FREE
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