On Statistical Learning for Individualized Decision Making with Complex Data

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• Chengchun Shi, London School of Economics
• Friday 07 February 2020, 14:00-15:00
• MR12.

If you have a question about this talk, please contact Dr Sergio Bacallado.

In this talk, I will present my research on individualized decision making with modern complex data. In precision medicine, individualizing the treatment decision rule can capture patients’ heterogeneous response towards treatment. In finance, individualizing the investment decision rule can improve individual’s financial well-being. In a ride-sharing company, individualizing the order dispatching strategy can increase its revenue and customer satisfaction. With the fast development of new technology, modern datasets often consist of massive observations, high-dimensional covariates and are characterized by some degree of heterogeneity. The talk is divided into two parts. In the first part, I will focus on the data heterogeneity and introduce a new maximin-projection learning for recommending an overall individualized decision rule based on the observed data from different populations with heterogeneity in optimal individualized decision making. In the second part, I will briefly summarize the statistical learning methods I’ve developed for individualized decision making with complex data.

This talk is part of the Statistics series.

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