2 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
Reconciling Heterogeneous Effects in Causal Inference
Audrey Chang, Emily Diana, Alexander Williams Tolbert
In this position and problem pitch paper, we offer a solution to the reference class problem in causal inference. We apply the Reconcile algorithm for model multiplicity in machine…
Correcting Underrepresentation and Intersectional Bias for Classification
Emily Diana, Alexander Williams Tolbert
We consider the problem of learning from data corrupted by underrepresentation bias, where positive examples are filtered from the data at different, unknown rates for a fixed numb…
Reconciling Individual Probability Forecasts
Aaron Roth, Alexander Tolbert, Scott Weinstein
Individual probabilities refer to the probabilities of outcomes that are realized only once: the probability that it will rain tomorrow, the probability that Alice will die within…