Results 21 to 30 of about 2,525,472 (291)
Computing Possible and Certain Answers over Order-Incomplete Data [PDF]
, 2019 This paper studies the complexity of query evaluation for databases whose relations are partially ordered; the problem commonly arises when combining or transforming ordered data from multiple sources.
Amarilli, Antoine +3 more
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Missing.... presumed at random: cost-analysis of incomplete data [PDF]
, 2002 When collecting patient-level resource use data for statistical analysis, for some patients and in some categories of resource use, the required count will not be observed. Although this problem must arise in most reported economic evaluations containing
Bang +31 more
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Analysis of Incomplete Data and an Intrinsic-Dimension Helly Theorem [PDF]
, 2008 The analysis of incomplete data is a long-standing challenge in practical statistics. When, as is typical, data objects are represented by points in R^d , incomplete data objects correspond to affine subspaces (lines or Δ-flats).With this motivation we ...
Gao, Jie +2 more
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Profile Likelihood and Incomplete Data [PDF]
International Statistical Review, 2010 Summary According to the law of likelihood, statistical evidence is represented by likelihood functions and its strength measured by likelihood ratios. This point of view has led to a likelihood paradigm for interpreting statistical evidence, which carefully distinguishes evidence about a parameter from error probabilities and personal belief.
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Textually Summarising Incomplete Data [PDF]
Proceedings of the 10th International Conference on Natural Language Generation, 2017 Many data-to-text NLG systems work with data sets which are incomplete, ie some of the data is missing. We have worked with data journalists to understand how they describe incomplete data, and are building NLG algorithms based on these insights. A pilot evaluation showed mixed results, and highlighted several areas where we need to improve our system.
Stephanie Inglis +2 more
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Uncovering Suspicious Activity From Partially Paired and Incomplete Multimodal Data
IEEE Access, 2017 Multimodal data can be used to gain additional perspective on a phenomenon. For applications, such as security and the detection of suspicious activity, the need to aggregate and analyze data from multiple modes is vital.
Carter Chiu, Justin Zhan, Felix Zhan
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Phase Identification With Incomplete Data
IEEE Transactions on Smart Grid, 2018 Phase identification is a process to determine which of the three phases a particular house is connected to. The state-of-the-art identification methods usually exploit smart metering data. However, the data sets are not always available and the major challenge is hence to identify phases with incomplete data set.
Minghao Xu, Ran Li 0004, Furong Li
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Applied Sciences, 2022 Feature selection has been widely used in machine learning and data mining since it can alleviate the burden of the so-called curse of dimensionality of high-dimensional data.
Jun Cai, Linge Fan, Xin Xu, Xinrong Wu
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Exploiting microvariation: How to make the best of your incomplete data [PDF]
, 2018 n this article we discuss the use of big corpuses or databases as a first step for qualitative analysis of linguistic data. We concentrate on ASIt, the Syntactic Atlas of Italy, and take into consideration the different types of dialectal data that can ...
Garzonio, Jacopo, Poletto, Cecilia
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Determining the Macroscopic Fundamental Diagram from Mixed and Partial Traffic Data
Promet (Zagreb), 2018 The macroscopic fundamental diagram (MFD) is a graphical method used to characterize the traffic state in a road network and to monitor and evaluate the effect of traffic management.
Yangbeibei Ji +3 more
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