منابع مشابه
Sparse Parameter Recovery from Aggregated Data
Data aggregation is becoming an increasingly common technique for sharing sensitive information, and for reducing data size when storage and/or communication costs are high. Aggregate quantities such as group-average are a form of semi-supervision as they do not directly provide information of individual values, but despite their wide-spread use, prior literature on learning individual-level mo...
متن کاملSparse Parameter Recovery from Aggregated Data : Supplement
To our knowledge, all prior work in the literature (eg. [Herman & Strohmer 2010; Chi et al. 2011; Rosenbaum et al. 2013; Rudelson & Zhou 2015] among others) only concern themselves with cases 1, 2 and 3. Moreover, for papers that do deal with case 2 and 3, unless s = 0 the existing analysis will be restricted to providing only approximate recovery guarantees. Thus, these methods do not apply di...
متن کاملModel Learning from Published Aggregated Data
In many application domains, particularly in healthcare, an access for individual datapoints is limited, while data aggregated in form of means and standard deviations are widely available. This limitation is a result of many factors, including privacy laws that prevent clinicians and scientists from freely sharing individual patient data, inability to share proprietary business data, and inade...
متن کاملEstimation of Individual Micro Data from Aggregated Open Data
In this paper, we propose a method of estimating individual micro data from aggregated open data based on semisupervised learning and conditional probability. Firstly, the proposed method collects aggregated open data and support data, which are related to the individual micro data to be estimated. Then, we perform the locality sensitive hashing (LSH) algorithm to find a subset of the support d...
متن کاملRunning head: CAUSAL INFERENCES FROM LONGITUDINAL DATA
Analyses of passive longitudinal data can yield causally relevant evidence only to the extent that plausible alternative explanations are ruled out. This study compared the ability of five types of longitudinal analyses to correct for selection biases confounded with corrective interventions, using a cohort of 1464 4and 5-year-olds from Canadian NLSCY data. Three lines of evidence indicated tha...
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ژورنال
عنوان ژورنال: Academic Emergency Medicine
سال: 2003
ISSN: 1069-6563
DOI: 10.1197/aemj.10.8.881