Cai, Tianxi

13 publications

ICML 2025 CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition Zebin Wang, Menghan Lin, Bolin Shen, Ken Anderson, Molei Liu, Tianxi Cai, Yushun Dong

JMLR 2025 Efficient and Robust Semi-Supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response Jue Hou, Rajarshi Mukherjee, Tianxi Cai

NeurIPS 2024 A Teacher-Teacher Framework for Clinical Language Representation Learning Feiqing Huang, Shenghan Zhang, Sara Morini Sweet, Tianxi Cai

JMLR 2023 Augmented Transfer Regression Learning with Semi-Non-Parametric Nuisance Models Molei Liu, Yi Zhang, Katherine P. Liao, Tianxi Cai

JMLR 2023 Multi-Source Learning via Completion of Block-Wise Overlapping Noisy Matrices Doudou Zhou, Tianxi Cai, Junwei Lu

JMLR 2023 Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee

JMLR 2023 Surrogate Assisted Semi-Supervised Inference for High Dimensional Risk Prediction Jue Hou, Zijian Guo, Tianxi Cai

JMLR 2022 Prior Adaptive Semi-Supervised Learning with Application to EHR Phenotyping Yichi Zhang, Molei Liu, Matey Neykov, Tianxi Cai

JMLR 2021 Integrative High Dimensional Multiple Testing with Heterogeneity Under Data Sharing Constraints Molei Liu, Yin Xia, Kelly Cho, Tianxi Cai

NeurIPS 2020 Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation Aaron Sonabend, Junwei Lu, Leo Anthony Celi, Tianxi Cai, Peter Szolovits

JMLR 2016 L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs Matey Neykov, Jun S. Liu, Tianxi Cai

JMLR 2016 On the Characterization of a Class of Fisher-Consistent Loss Functions and Its Application to Boosting Matey Neykov, Jun S. Liu, Tianxi Cai

JMLR 2008 Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers Bo Jiang, Xuegong Zhang, Tianxi Cai