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We live in the Information Era, with access to a huge amount of information from a variety of data sources. However, data sources are of different qualities, often providing con�...
We continue our recent work on finite-sample, i.e., non-asymptotic, inference with two-step, monotone incomplete data from Nd(µ, Σ), a multivariate normal population with mean ...
Parametric models for estimating network link delays with incomplete data that incorporate spatial correlation are formulated. Fast numerical methods for estimation of parameters ...
Based on independent component analysis (ICA) and self-organizing maps (SOM), this paper proposes an ISOM-DH model for the incomplete data’s handling in data mining. Under these ...
A probabilistic wavelet system (PWS) is proposed to model the unknown dynamic system with stochastic and incomplete data. When compared with the traditional wavelet system, the PWS...
Industrial databases often contain a large amount of unfilled information. During the knowledge discovery process one processing step is often necessary in order to remove these ...
This paper addresses the following question: how should we update our beliefs after observing some incomplete data, in order to make credible predictions about new, and possibly i...
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
There has been a recent resurgence of interest in research on noisy and incomplete data. Many applications require information to be recovered from such data. For example, in sens...
Junyi Xie, Jun Yang 0001, Yuguo Chen, Haixun Wang,...