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09/03/2023
Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation
"Clipping" (a.k.a. importance weight truncation) is a widely used varian...
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10/15/2022
Fair Effect Attribution in Parallel Online Experiments
A/B tests serve the purpose of reliably identifying the effect of change...
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05/12/2022
Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling
The Plackett-Luce (PL) model is ubiquitous in learning-to-rank (LTR) bec...
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07/28/2021
Ranker-agnostic Contextual Position Bias Estimation
Learning-to-rank (LTR) algorithms are ubiquitous and necessary to explor...
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10/17/2018
Hierarchical Methods of Moments
Spectral methods of moments provide a powerful tool for learning the par...
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07/04/2018
Generating Synthetic but Plausible Healthcare Record Datasets
Generating datasets that "look like" given real ones is an interesting t...
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08/29/2017