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Małgorzata Bogdan – Recent developments on Sorted L-One Penalized Estimation

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A month ago we finished Why R? 2020 conference. We had an pleasure to host Małgorzata Bogdan, an associate professor of statistics at University of Wrocław. This post contains a biography of the speaker and an abstract of her talk: Recent developments on Sorted L-One Penalized Estimation.

Sorted L-One Penalized Estimator is an extension of LASSO, which allows for a reduction of dimension by eliminating some of the model parameters as well as by making some of them equal to each other. In this talk we will present some of the recent developments on SLOPE, with the specific emphasis on the Adaptive Bayesian version of SLOPE and on the strong screening rule, which allows a substantial speeding up of the SLOPE algorithm.

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Małgorzata Bodgan is an associate professor of statistics at University of Wrocław. She focuses on statistical methods for filtering and modeling high-dimension data. She conducted her research at University of Washington, Purdue University, University of Vienna, Lund University and Stanford University. Małgorzata has published over fifty scientific publications and her achievements earned her a “Women for Math Science Award” from the Department of Mathematics of Munich University of Technology and Fullbright Scholarship.

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