2 citations · 5 across the 8 of their papers we have counts for
3 papers · 1 filter
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
Jacqueline Maasch, Weishen Pan, Shantanu Gupta +3
Causal discovery is crucial for causal inference in observational studies, as it can enable the identification of valid adjustment sets (VAS) for unbiased effect estimation. Howeve…
Anytime-valid inference in N-of-1 trials
Ivana Malenica, Yongyi Guo, Kyra Gan +1
App-based N-of-1 trials offer a scalable experimental design for assessing the effects of health interventions at an individual level. Their practical success depends on the strong…
Contextual Bandits with Budgeted Information Reveal
Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu +1
Contextual bandit algorithms are commonly used in digital health to recommend personalized treatments. However, to ensure the effectiveness of the treatments, patients are often re…