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    • 88. 发明授权
    • Distributed reservoir sampling for web applications
    • Web应用程序的分布式油藏采样
    • US07308447B2
    • 2007-12-11
    • US11212301
    • 2005-08-26
    • David M. ChickeringAshis K. RoyChristopher A. Meek
    • David M. ChickeringAshis K. RoyChristopher A. Meek
    • G06F17/30
    • G06F17/30861Y10S707/99936
    • Random samples without replacement are extracted from a distributed set of items by leveraging techniques for aggregating sampled subsets of the distributed set. This provides a uniform random sample without replacement representative of the distributed set, allowing statistical information to be gleaned from extremely large sets of distributed information. Subset random samples without replacement are extracted from independent subsets of the distributed set of items. The subset random samples are then aggregated to provide a uniform random sample without replacement of a fixed size that is representative of a distributed set of items of unknown size. In one instance, a multivariate hyper-geometric distribution is sampled by breaking up the multivariate hyper-geometric distribution into a set of univariate hyper-geometric distributions. Individual items of a uniform random sample without replacement are then determined utilizing a normal approximation of the univariate hyper-geometric distributions and a finite population correction factor.
    • 通过利用用于聚合分布集合的采样子集的技术,从分布式集合中提取不带替换的随机样本。 这提供了一个统一的随机样本,而不需要替代代表分布集,允许从极大的分布式信息集中收集统计信息。 从分配的项目集的独立子集中提取不具有替换的子集随机样本。 然后将子集随机样本聚合以提供均匀的随机样本,而不替换代表未知大小的分布式项目集合的固定大小。 在一种情况下,通过将多变量超几何分布分解成一组单变量超几何分布来对多变量超几何分布进行采样。 然后使用单变量超几何分布的正态近似和有限群体校正因子来确定不具有替换的均匀随机样本的单个项目。
    • 90. 发明授权
    • Staged mixture modeling
    • 分阶段混合建模
    • US07133811B2
    • 2006-11-07
    • US10270914
    • 2002-10-15
    • Bo ThiessonChristopher A. MeekDavid E. Heckerman
    • Bo ThiessonChristopher A. MeekDavid E. Heckerman
    • G06F17/10
    • G06K9/6226G06F17/18Y10S707/99935Y10S707/99936Y10S707/99942
    • A system and method for generating staged mixture model(s) is provided. The staged mixture model includes a plurality of mixture components each having an associated mixture weight, and, an added mixture component having an initial structure, parameters and associated mixture weight. The added mixture component is modified based, at least in part, upon a case that is undesirably addressed by the plurality of mixture components using a structural expectation maximization (SEM) algorithm to modify at the structure, parameters and/or associated mixture weight of the added mixture component.The staged mixture model employs a data-driven staged mixture modeling technique, for example, for building density, regression, and classification model(s). The basic approach is to add mixture component(s) (e.g., sequentially) to the staged mixture model using an SEM algorithm.
    • 提供了一种用于生成分段混合模型的系统和方法。 分级混合物模型包括各自具有相关混合物重量的多种混合物组分,以及具有初始结构,参数和相关混合物重量的添加的混合物组分。 至少部分地,添加的混合物组分基于使用结构期望最大化(SEM)算法不期望地由多个混合物组分解决的情况进行修饰,以在结构,参数和/或相关联的混合物重量 加入的混合物组分。 分级混合模型采用数据驱动的分段混合建模技术,例如建筑密度,回归和分类模型。 基本方法是使用SEM算法将混合物组分(例如,顺序地)添加到分级混合物模型中。