4 papers
Fixed-Size Active Statistical Inference
Erik Skalnes, Michael Oberst
Variance reduction techniques improve the efficiency of drawing conclusions from data. Recent proposals for variance-reduction use two complementary techniques to reduce variance:…
Evaluating Rubric Generation with Interventional Transfer
Erik Skalnes, Layne C. Price, Raviteja Anantha +1
Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale, prompting research into the…
Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness
Jonathan Zhang, Erik Skalnes, Jacob Chen +1
Predictive machine learning (ML) models are increasingly used to aid human decision-makers across various high-risk domains such as healthcare and criminal justice. There is a grow…
Sequential Counterfactual Decision-Making Under Confounded Reward
Erik Skalnes
We investigate the limitations of random trials when the cause of interest is confounded with the effect by formalizing a counterfactual policy-space where the agent's natural pred…