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10/25/2022
Improving Group Lasso for high-dimensional categorical data
Sparse modelling or model selection with categorical data is challenging...
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09/16/2022
Joint estimation of posterior probability and propensity score function for positive and unlabelled data
Positive and unlabelled learning is an important problem which arises na...
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12/21/2021
Group Lasso merger for sparse prediction with high-dimensional categorical data
Sparse prediction with categorical data is challenging even for a modera...
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06/13/2020
Structure learning for CTBN's via penalized maximum likelihood methods
The continuous-time Bayesian networks (CTBNs) represent a class of stoch...
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07/05/2019
Improving Lasso for model selection and prediction
It is known that the Thresholded Lasso (TL), SCAD or MCP correct intrins...
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05/14/2019
Fast and robust model selection based on ranks
We consider the problem of identifying important predictors in large dat...
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08/08/2018
Asymptotics of maximum likelihood estimators based on Markov chain Monte Carlo methods
In many complex statistical models maximum likelihood estimators cannot ...
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12/17/2015