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The Conflict Graph Design: Estimating Causal Effects Under Interference
On November 1, 2024 at 11:00 am till 12:00 pm E18-304Christopher Harshaw, Columbia University
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A Flexible Defense Against the Winner’s Curse
On October 25, 2024 at 11:00 am till 12:00 pm E18-304Abstract: Across science and policy, decision-makers often need to draw conclusions about the best candidate among competing alternatives. For instance, researchers may seek to infer the effectiveness of the most successful treatment or determine which demographic group benefits most from a specific treatment. Similarly, in machine learning, practitioners are often interested in the population performance of…
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Sampling through optimization of divergences on the space of measures
On October 18, 2024 at 11:00 am till 12:00 pm E18-304Anna Korba, ENSAE/CREST
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Central Limit Theorems for Smooth Optimal Transport Maps
On October 11, 2024 at 11:00 am till 12:00 pm E18-304Tudor Manole, MIT
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Trees and V’s: Inference for Ensemble Models
On October 4, 2024 at 11:00 am till 12:00 pm E18-304Abstract: This talk discusses uncertainty quantification and inference using ensemble methods. Recent theoretical developments inspired by random forests have cast bagging-type methods as U-statistics when bootstrap samples are replaced by subsamples, resulting in a central limit theorem and hence the potential for inference. However, to carry this out requires estimating a variance for which all…
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Large cycles for the interchange process
On September 27, 2024 at 11:00 am till 12:00 pm E18-304Allan Sly, Princeton University
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Model-agnostic covariate-assisted inference on partially identified causal effects
On September 13, 2024 at 11:00 am till 12:00 pm E18-304Lihua Lei, Stanford University
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Bias Reduction and Asymptotic Efficiency in Estimation of Smooth Functionals of High-Dimensional Covariance
On November 30, 2018 at 12:00 am till 11:00 am E18-304Vladimir Koltchinskii (Georgia Institute of Technology)
