Kyra Gan

According to our database, Kyra Gan authored at least 20 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

When Additive Noise Meets Unobserved Mediators: Bivariate Denoising Diffusion for Causal Discovery.

Dominik Meier, Sujai Hiremath, Promit Ghosal, Kyra Gan

CoRR, June, 2025

Federated Causal Inference in Healthcare: Methods, Challenges, and Applications.

Haoyang Li, Jie Xu, Kyra Gan, Fei Wang, Chengxi Zang

CoRR, May, 2025

MOSIC: Model-Agnostic Optimal Subgroup Identification with Multi-Constraint for Improved Reliability.

Wenxin Chen, Weishen Pan, Kyra Gan, Fei Wang

CoRR, April, 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, February, 2025

LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery.

Sujai Hiremath, Promit Ghosal, Kyra Gan

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 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

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

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

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

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

Hybrid Global Causal Discovery with Local Search.

Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao, Promit Ghosal, Kyra Gan

CoRR, 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

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

Proceedings of the Uncertainty in Artificial Intelligence, 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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams.

Brian Cho, Kyra Gan, Nathan Kallus

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Contextual Bandits with Budgeted Information Reveal.

Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan A. Murphy

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Anytime-valid inference in N-of-1 trials.

Ivana Malenica, Yongyi Guo, Kyra Gan, Stefan Konigorski

Proceedings of the Machine Learning for Health, 2023

2021

Approximation Algorithms for Active Sequential Hypothesis Testing.

Kyra Gan, Su Jia, Andrew A. Li

CoRR, 2021

Greedy Approximation Algorithms for Active Sequential Hypothesis Testing.

Kyra Gan, Su Jia, Andrew A. Li

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Causal Inference with Selectively Deconfounded Data.

Kyra Gan, Andrew A. Li, Zachary Chase Lipton, Sridhar R. Tayur

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021