Causal Inference with Selectively Deconfounded Data. - Kyra Gan; Andrew A. Li; Zachary Chase Lipton; Sridhar R. Tayur (AISTATS, 2021)

Greedy Approximation Algorithms for Active Sequential Hypothesis Testing. - Kyra Gan; Su Jia; Andrew A. Li (NeurIPS, 2021)

Approximation Algorithms for Active Sequential Hypothesis Testing. - Kyra Gan; Su Jia; Andrew A. Li (CoRR, 2021)

Anytime-valid inference in N-of-1 trials. - Ivana Malenica; Yongyi Guo; Kyra Gan; Stefan Konigorski (ML4H@NeurIPS, 2023)

Contextual Bandits with Budgeted Information Reveal. - Kyra Gan; Esmaeil Keyvanshokooh; Xueqing Liu; Susan A. Murphy (AISTATS, 2024)

Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams. - Brian Cho 001; Kyra Gan; Nathan Kallus (ICML, 2024)

Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters. - Brian M. Cho; Yaroslav Mukhin; Kyra Gan; Ivana Malenica (ICML, 2024)

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; Promit Ghosal; Kyra Gan (NeurIPS, 2024)

Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. - Jacqueline R. M. A. Maasch; Weishen Pan; Shantanu Gupta; Volodymyr Kuleshov; Kyra Gan; Fei Wang 001 (UAI, 2024)

Online Uniform Risk Times Sampling: First Approximation Algorithms, Learning Augmentation with Full Confidence Interval Integration. - Xueqing Liu; Kyra Gan; Esmaeil Keyvanshokooh; Susan A. Murphy (CoRR, 2024)

Hybrid Global Causal Discovery with Local Search. - Sujai Hiremath; Jacqueline R. M. A. Maasch; Mengxiao Gao; Promit Ghosal; Kyra Gan (CoRR, 2024)

LoSAM: Local Search in Additive Noise Models with Unmeasured Confounders, a Top-Down Global Discovery Approach. - Sujai Hiremath; Promit Ghosal; Kyra Gan (CoRR, 2024)

Local Causal Discovery for Structural Evidence of Direct Discrimination. - Jacqueline R. M. A. Maasch; Kyra Gan; Violet Chen; Agni Orfanoudaki; Nil-Jana Akpinar; Fei Wang 001 (AAAI, 2025)

Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits. - Brian M. Cho; Dominik Meier; Kyra Gan; Nathan Kallus (AISTATS, 2025)

CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies. - Brian M. Cho; Ana-Roxana Pop; Kyra Gan; Sam Corbett-Davies; Israel Nir; Ariel Evnine; Nathan Kallus (KDD (1), 2025)

LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery. - Sujai Hiremath; Promit Ghosal; Kyra Gan (UAI, 2025)

From Restless to Contextual: A Thresholding Bandit Approach to Improve Finite-horizon Performance. - Jiamin Xu; Ivan Nazarov; Aditya Rastogi; África Periáñez; Kyra Gan (CoRR, 2025)

MOSIC: Model-Agnostic Optimal Subgroup Identification with Multi-Constraint for Improved Reliability. - Wenxin Chen; Weishen Pan; Kyra Gan; Fei Wang 001 (CoRR, 2025)

Federated Causal Inference in Healthcare: Methods, Challenges, and Applications. - Haoyang Li 001; Jie Xu 012; Kyra Gan; Fei Wang 001; Chengxi Zang (CoRR, 2025)

When Additive Noise Meets Unobserved Mediators: Bivariate Denoising Diffusion for Causal Discovery. - Dominik Meier; Sujai Hiremath; Promit Ghosal; Kyra Gan (CoRR, 2025)