Examples with "using a sparse bayesian model" and their translation in Chinees
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Using a sparse Bayesian model, our proposed method obtains an estimate of the abundance fraction vector with only a few nonzero entries, and the zero entries of the estimate can be interpreted as the absence of certain agents.
In Section II, the agent identification scheme using a sparse Bayesian model is described, along with a discussion on how to address the issue of signature mismatch.
In our numerical studies, the abundance fractions of agents are estimated by the following methods: the sparse Bayesian model (SBM) using the noninformative hyperprior and taking into account the nonnegativity of the abundance fractions, as described in Section II-D, the NCLS algorithm and the orthogonal matching pursuit (OMP) method.
situation-dependent information extraction, using Bayesian networks, statistical analyses, and hidden Markov models to extract meaning and context from complex and cluttered data streams drawn from very disparate sensors that are not temporally or spatially matched
The Word Sense Disambiguation (WSD) study based on large scale real world corpus is performed using an unsupervised learning algorithm based on DGA improved Bayesian Model.
Compared with the Bayesian model using the Laplacian prior and the -norm constrained minimization (5), which have to tune some parameters during estimation, the Bayesian model using the noninformative hyperprior can estimate all the parameters automatically.
The Division extended its methodological work on family planning using a Bayesian hierarchical model combined with country-specific time trends and produced a unique, publicly available set of long-term estimates and projections of contraceptive prevalence, unmet need for family planning, total demand for family planning and percentage of demand for family planning that is satisfied among married or in-union women from 1970 to 2030.
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