Kyra Gan - RankMe

31 papers A* 5A 5Journal 19Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep Doubly Debiased Longitudinal Effect Estimation with ICE G-Computation. CoRR Wenxin Chen, Weishen Pan, Kyra Gan, Fei Wang
2026	J	`jnl`	Fast Non-Episodic Finite-Horizon RL with K-Step Lookahead Thresholding. CoRR Jiamin Xu, Kyra Gan
2025	—	`conf`	CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies. KDD (1) Brian M. Cho, Ana-Roxana Pop, Kyra Gan, Sam Corbett-Davies, Israel Nir, Ariel Evnine, Nathan Kallus
2025	J	`jnl`	Clustering by Denoising: Latent plug-and-play diffusion for single-cell data. CoRR Dominik Meier, Shixing Yu, Sagnik Nandy, Promit Ghosal, Kyra Gan
2025	J	`jnl`	Federated Causal Inference in Healthcare: Methods, Challenges, and Applications. CoRR Haoyang Li, Jie Xu, Kyra Gan, Fei Wang, Chengxi Zang
2025	J	`jnl`	From Guess2Graph: When and How Can Unreliable Experts Safely Boost Causal Discovery in Finite Samples? CoRR Sujai Hiremath, Dominik Janzing, Philipp Michael Faller, Patrick Blöbaum, Elke Kirschbaum, Shiva Prasad Kasiviswanathan, Kyra Gan
2025	J	`jnl`	From Restless to Contextual: A Thresholding Bandit Approach to Improve Finite-horizon Performance. CoRR Jiamin Xu, Ivan Nazarov, Aditya Rastogi, África Periáñez, Kyra Gan
2025	A	`conf`	LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery. UAI Sujai Hiremath, Promit Ghosal, Kyra Gan
2025	A*	`conf`	Local Causal Discovery for Structural Evidence of Direct Discrimination. AAAI Jacqueline R. M. A. Maasch, Kyra Gan, Violet Chen, Agni Orfanoudaki, Nil-Jana Akpinar, Fei Wang
2025	J	`jnl`	MOSIC: Model-Agnostic Optimal Subgroup Identification with Multi-Constraint for Improved Reliability. CoRR Wenxin Chen, Weishen Pan, Kyra Gan, Fei Wang
2025	A	`conf`	Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits. AISTATS Brian M. Cho, Dominik Meier, Kyra Gan, Nathan Kallus
2025	J	`jnl`	When Additive Noise Meets Unobserved Mediators: Bivariate Denoising Diffusion for Causal Discovery. CoRR Dominik Meier, Sujai Hiremath, Promit Ghosal, Kyra Gan
2024	J	`jnl`	CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies. CoRR Brian M. Cho, Ana-Roxana Pop, Kyra Gan, Sam Corbett-Davies, Israel Nir, Ariel Evnine, Nathan Kallus
2024	A	`conf`	Contextual Bandits with Budgeted Information Reveal. AISTATS Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan A. Murphy
2024	J	`jnl`	Hybrid Global Causal Discovery with Local Search. CoRR Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao, Promit Ghosal, Kyra Gan
2024	A*	`conf`	Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models. NeurIPS Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao, Promit Ghosal, Kyra Gan
2024	A*	`conf`	Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters. ICML Brian M. Cho, Yaroslav Mukhin, Kyra Gan, Ivana Malenica
2024	J	`jnl`	LoSAM: Local Search in Additive Noise Models with Unmeasured Confounders, a Top-Down Global Discovery Approach. CoRR Sujai Hiremath, Promit Ghosal, Kyra Gan
2024	J	`jnl`	Local Causal Discovery for Structural Evidence of Direct Discrimination. CoRR Jacqueline R. M. A. Maasch, Kyra Gan, Violet Chen, Agni Orfanoudaki, Nil-Jana Akpinar, Fei Wang
2024	A	`conf`	Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. UAI Jacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang
2024	J	`jnl`	Online Uniform Risk Times Sampling: First Approximation Algorithms, Learning Augmentation with Full Confidence Interval Integration. CoRR Xueqing Liu, Kyra Gan, Esmaeil Keyvanshokooh, Susan A. Murphy
2024	A*	`conf`	Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams. ICML Brian Cho, Kyra Gan, Nathan Kallus
2024	J	`jnl`	Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams. CoRR Brian Cho, Kyra Gan, Nathan Kallus
2024	J	`jnl`	Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits. CoRR Brian Cho, Dominik Meier, Kyra Gan, Nathan Kallus
2023	—	`conf`	Anytime-valid inference in N-of-1 trials. ML4H@NeurIPS Ivana Malenica, Yongyi Guo, Kyra Gan, Stefan Konigorski
2023	J	`jnl`	Contextual Bandits with Budgeted Information Reveal. CoRR Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan A. Murphy
2023	J	`jnl`	Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. CoRR Jacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang
2021	J	`jnl`	Approximation Algorithms for Active Sequential Hypothesis Testing. CoRR Kyra Gan, Su Jia, Andrew A. Li
2021	A	`conf`	Causal Inference with Selectively Deconfounded Data. AISTATS Kyra Gan, Andrew A. Li, Zachary Chase Lipton, Sridhar R. Tayur
2021	A*	`conf`	Greedy Approximation Algorithms for Active Sequential Hypothesis Testing. NeurIPS Kyra Gan, Su Jia, Andrew A. Li
2020	J	`jnl`	Causal Inference With Selectively-Deconfounded Data. CoRR Kyra Gan, Andrew A. Li, Zachary C. Lipton, Sridhar R. Tayur