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A network-constrain Weibull AFT model for biomarkers discovery
We propose AFTNet, a novel network-constraint survival analysis method based on the Weibull accelerated failure time (AFT) model solved by a penalized likelihood approach for variable selection and estimation.
A global approach for learning sparse Ising models
We consider the problem of learning the link parameters as well as the structure of a binary-valued pairwise Markov model.
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