2 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models
Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao +2
Learning the unique directed acyclic graph corresponding to an unknown causal model is a challenging task. Methods based on functional causal models can identify a unique graph, bu…
Online Uniform Sampling: Randomized Learning-Augmented Approximation Algorithms with Application to Digital Health
Xueqing Liu, Kyra Gan, Esmaeil Keyvanshokooh +1
Motivated by applications in digital health, this work studies the novel problem of online uniform sampling (OUS), where the goal is to distribute a sampling budget uniformly acros…
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…
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
Kyra Gan, Su Jia, Andrew Li
In the problem of active sequential hypothesis testing (ASHT), a learner seeks to identify the true hypothesis from among a known set of hypotheses. The learner is given a set of a…