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Statistics Department Seminar Series: Jelena Bradic, Associate Professor of Mathematics, University of California San Diego

"Causal Learning: excursions in double robustness"
Friday, October 23, 2020
10:00-11:00 AM
Off Campus Location
Recent progress in machine learning provides many potentially effective tools to learn estimates or make predictions from datasets of ever-increasing sizes. Can we trust such tools in clinical and highly-sensitive systems? If a learning algorithm predicts an effect of a new policy to be positive, what guarantees do we have concerning the accuracy of this prediction? The talk introduces new statistical ideas to ensure that the learned estimates satisfy some fundamental properties: especially causality and robustness. The talk will discuss potential connections and departures between causality and robustness.

Jelena Bradic received her Ph.D. in Operations Research and Financial Engineering from Princeton in Spring 2011 with a specialization in Statistics and Applied Probability under the direction of Jianqing Fan. Her research is in high dimensional statistics, stochastic optimization, asymptotic theory, robust statistics, functional genomics and biostatistics. She has received two teaching awards (for teaching assistants) at Princeton.

This seminar will be livestreamed via Zoom
There will be a virtual reception to follow.
Building: Off Campus Location
Location: Virtual
Event Type: Workshop / Seminar
Tags: seminar
Source: Happening @ Michigan from Department of Statistics Seminar Series, Department of Statistics