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基于模式导向抽样的大规模数据流监测AI 解读

Monitoring large-scale datastreams with limited resources has become increasingly important for real-time detection of abnormal activities in many applications. Despite the availability of large datasets, the challenges associated with designing an efficient change-detection when clustering or spatial pattern exists are not yet well addressed. In this article, a design-adaptive testing procedure is developed when only a limited number of streaming observations can be…

基于 Itô–Taylor 展开的多元扩散新型 delta 展开AI 解读

In this paper we develop a new delta expansion approach to deriving analytical approximation to the transition densities of multivariate diffusions using the Itô-Taylor expansion of the conditional expectation of the Dirac delta function. Our approach yields an explicit recursive formulas for the expansion coefficients and is universally applicable for a wide spectrum of models, particularly the time-inhomogeneous non-affine irreducible multivariate diffusions. We show that…