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03/21/2023
Adaptive Experimentation at Scale: Bayesian Algorithms for Flexible Batches
Standard bandit algorithms that assume continual reallocation of measure...
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03/10/2022
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
The conventional recipe for maximizing model accuracy is to (1) train mu...
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09/04/2021
Robust fine-tuning of zero-shot models
Large pre-trained models such as CLIP offer consistent accuracy across a...
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07/05/2020
Robust Causal Inference Under Covariate Shift via Worst-Case Subpopulation Treatment Effects
We propose the worst-case treatment effect (WTE) across all subpopulatio...
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08/28/2018
Bounds on the conditional and average treatment effect in the presence of unobserved confounders
The causal effect of an intervention can not be consistently estimated w...
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05/30/2018
Generalizing to Unseen Domains via Adversarial Data Augmentation
We are concerned with learning models that generalize well to different ...
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10/11/2016
