13 citations · 14 across the 8 of their papers we have counts for
3 papers · 1 filter
Improving the Efficiency of the PC Algorithm by Using Model-Based Conditional Independence Tests
Erica Cai, Andrew McGregor, David Jensen
Learning causal structure is useful in many areas of artificial intelligence, including planning, robotics, and explanation. Constraint-based structure learning algorithms such as…
Adaptive Selection of the Optimal Strategy to Improve Precision and Power in Randomized Trials
Laura B. Balzer, Erica Cai, Lucas Godoy Garraza +1
Benkeser et al. demonstrate how adjustment for baseline covariates in randomized trials can meaningfully improve precision for a variety of outcome types. Their findings build on a…
Measuring Interventional Robustness in Reinforcement Learning
Katherine Avery, Jack Kenney, Pracheta Amaranath +2
Recent work in reinforcement learning has focused on several characteristics of learned policies that go beyond maximizing reward. These properties include fairness, explainability…