Molei Liu - RankMe

27 papers A* 3Misc 1Journal 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adversarial Drift-Aware Predictive Transfer: Toward Durable Clinical AI. CoRR Xin Xiong, Zijian Guo, Haobo Zhu, Chuan Hong, Jordan W. Smoller, Tianxi Cai, Molei Liu
2026	J	`jnl`	Maximin Learning of Individualized Treatment Effect on Multi-Domain Outcomes. CoRR Yuying Lu, Wenbo Fei, Yuanjia Wang, Molei Liu
2026	J	`jnl`	SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs. Bioinform. Alex Rodriguez, Youngdae Kim, Tarak Nath Nandi, Karl Keat, Rachit Kumar, Mitchell Conery, Rohan Bhukar, Molei Liu, John Hessington, Ketan Maheshwari, VA Million Veteran Program, Edmon Begoli, Georgia Tourassi, Pradeep Natarajan, Benjamin F. Voight, John Michael Gaziano, Scott M. Damrauer, Katherine P. Liao, Wei Zhou, Jennifer E. Huffman, Anurag Verma, Ravi K. Madduri
2025	A*	`conf`	CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition. ICML Zebin Wang, Menghan Lin, Bolin Shen, Ken Anderson, Molei Liu, Tianxi Cai, Yushun Dong
2025	J	`jnl`	CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition. CoRR Zebin Wang, Menghan Lin, Bolin Shen, Ken Anderson, Molei Liu, Tianxi Cai, Yushun Dong
2025	J	`jnl`	FedIMPUTE: Privacy-preserving missing value imputation for multi-site heterogeneous electronic health records. J. Biomed. Informatics Siqi Li, Mengying Yan, Ruizhi Yuan, Molei Liu, Nan Liu, Chuan Hong
2025	A*	`conf`	Knowledge-Guided Wasserstein Distributionally Robust Optimization. ICML Zitao Wang, Ziyuan Wang, Molei Liu, Nian Si
2025	J	`jnl`	Knowledge-Guided Wasserstein Distributionally Robust Optimization. CoRR Zitao Wang, Ziyuan Wang, Molei Liu, Nian Si
2025	J	`jnl`	RELEAP: Reinforcement-Enhanced Label-Efficient Active Phenotyping for Electronic Health Records. CoRR Yang Yang, Kathryn I. Pollak, Bibhas Chakraborty, Molei Liu, Doudou Zhou, Chuan Hong
2025	J	`jnl`	Representation-Aware Distributionally Robust Optimization: A Knowledge Transfer Framework. CoRR Zitao Wang, Nian Si, Molei Liu
2025	J	`jnl`	Robust Mixture Models for Algorithmic Fairness Under Latent Heterogeneity. CoRR Siqi Li, Molei Liu, Ziye Tian, Chuan Hong, Nan Liu
2025	J	`jnl`	SIM-Shapley: A Stable and Computationally Efficient Approach to Shapley Value Approximation. CoRR Wangxuan Fan, Siqi Li, Doudou Zhou, Yohei Okada, Chuan Hong, Molei Liu, Nan Liu
2025	J	`jnl`	Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data. CoRR Linshanshan Wang, Mengyan Li, Zongqi Xia, Molei Liu, Tianxi Cai
2025	J	`jnl`	StablePCA: Learning Shared Representations across Multiple Sources via Minimax Optimization. CoRR Zhenyu Wang, Molei Liu, Jing Lei, Francis Bach, Zijian Guo
2025	J	`jnl`	TRACER: Transfer Learning based Real-time Adaptation for Clinical Evolving Risk. CoRR Mengying Yan, Ziye Tian, Siqi Li, Nan Liu, Benjamin Goldstein, Molei Liu, Chuan Hong
2025	J	`jnl`	Transfer Learning of CATE with Kernel Ridge Regression. CoRR Seok-Jin Kim, HongJie Liu, Molei Liu, Kaizheng Wang
2024	J	`jnl`	Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis. CoRR Siqi Li, Xin Li, Kunyu Yu, Di Miao, Mingcheng Zhu, Mengying Yan, Yuhe Ke, Danny D'Agostino, Yilin Ning, Qiming Wu, Ziwen Wang, Yuqing Shang, Molei Liu, Chuan Hong, Nan Liu
2024	A*	`conf`	Covariate Shift Corrected Conditional Randomization Test. NeurIPS Bowen Xu, Yiwen Huang, Chuan Hong, Shuangning Li, Molei Liu
2024	J	`jnl`	Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance. J. Biomed. Informatics Chuan Hong, Molei Liu, Daniel Wojdyla, Jimmy Hickey, Michael J. Pencina, Ricardo Henao
2023	J	`jnl`	Augmented Transfer Regression Learning with Semi-non-parametric Nuisance Models. J. Mach. Learn. Res. Molei Liu, Yi Zhang, Katherine P. Liao, Tianxi Cai
2022	Misc	`conf`	Knowledge-Driven Online Multimodal Automated Phenotyping System. AMIA Molei Liu, Sara Morini, Xin Xiong, Chuan Hong, Clara-Lea Bonzel, Vidul Ayakulangara Panickan, Everett Neil Rush, Yuk-Lam Ho, Kelly Cho, John Michael Gaziano, Katherine P. Liao, Tianxi Cai, Tianrun Cai
2022	J	`jnl`	Prior Adaptive Semi-supervised Learning with Application to EHR Phenotyping. J. Mach. Learn. Res. Yichi Zhang, Molei Liu, Matey Neykov, Tianxi Cai
2022	J	`jnl`	Weakly Semi-supervised phenotyping using Electronic Health records. J. Biomed. Informatics Isabelle-Emmanuella Nogues, Jun Wen, Yucong Lin, Molei Liu, Sara K. Tedeschi, Alon Geva, Tianxi Cai, Chuan Hong
2021	J	`jnl`	A high-throughput phenotyping algorithm is portable from adult to pediatric populations. J. Am. Medical Informatics Assoc. Alon Geva, Molei Liu, Vidul Ayakulangara Panickan, Paul Avillach, Tianxi Cai, Kenneth D. Mandl
2021	J	`jnl`	Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data. npj Digit. Medicine Chuan Hong, Everett Neil Rush, Molei Liu, Doudou Zhou, Jiehuan Sun, Aaron Sonabend W., Victor M. Castro, Petra Schubert, Vidul Ayakulangara Panickan, Tianrun Cai, Lauren Costa, Zeling He, Nicholas B. Link, Ronald G. Hauser, John Michael Gaziano, Shawn N. Murphy, George Ostrouchov, Yuk-Lam Ho, Edmon Begoli, Junwei Lu, Kelly Cho, Katherine P. Liao, Tianxi Cai
2021	J	`jnl`	Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints. J. Mach. Learn. Res. Molei Liu, Yin Xia, Kelly Cho, Tianxi Cai
2020	J	`jnl`	Efficient Estimation and Evaluation of Prediction Rules in Semi-Supervised Settings under Stratified Sampling. CoRR Jessica L. Gronsbell, Molei Liu, Lu Tian, Tianxi Cai