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  1. No Access

    Article

    Convex clustering for binary data

    We present a new clustering algorithm for multivariate binary data. The new algorithm is based on the convex relaxation of hierarchical clustering, which is achieved by considering the binomial likelihood as a...

    Hosik Choi, Seokho Lee in Advances in Data Analysis and Classification (2019)

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    Article

    Marginalized lasso in sparse regression

    We propose marginalized lasso, a new nonconvex penalization for variable selection in regression problem. The marginalized lasso penalty is motivated from integrating out the penalty parameter in the original ...

    Seokho Lee, Seonhwa Kim in Journal of the Korean Statistical Society (2019)

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    Article

    A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood

    We propose a new biclustering method for binary data matrices using the maximum penalized Bernoulli likelihood estimation. Our method applies a multi-layer model defined on the logits of the success probabilit...

    Seokho Lee, Jianhua Z. Huang in Statistics and Computing (2014)