Liu, Anqi

31 publications

TMLR 2025 A Unified View of Double-Weighting for Marginal Distribution Shift José I. Segovia-Martín, Santiago Mazuelas, Anqi Liu

NeurIPS 2025 Conformal Linguistic Calibration: Trading-Off Between Factuality and Specificity Zhengping Jiang, Anqi Liu, Benjamin Van Durme

UAI 2025 ODD: Overlap-Aware Estimation of Model Performance Under Distribution Shift Aayush Mishra, Anqi Liu

AISTATS 2025 Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits Ha Manh Bui, Enrique Mallada, Anqi Liu

ICML 2025 WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales Drew Prinster, Xing Han, Anqi Liu, Suchi Saria

ICLR 2024 ADOPD: A Large-Scale Document Page Decomposition Dataset Jiuxiang Gu, Xiangxi Shi, Jason Kuen, Lu Qi, Ruiyi Zhang, Anqi Liu, Ani Nenkova, Tong Sun

ICML 2024 Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them) Drew Prinster, Samuel Don Stanton, Anqi Liu, Suchi Saria

AISTATS 2024 Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation Under Distribution Shifts Ha Manh Bui, Anqi Liu

ICML 2024 Density-SoftMax: Efficient Test-Time Model for Uncertainty Estimation and Robustness Under Distribution Shifts Ha Manh Bui, Anqi Liu

TMLR 2024 Distributionally Robust Policy Evaluation Under General Covariate Shift in Contextual Bandits Yihong Guo, Hao Liu, Yisong Yue, Anqi Liu

NeurIPS 2024 Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation Yihong Guo, Yixuan Wang, Yuanyuan Shi, Pan Xu, Anqi Liu

NeurIPS 2024 SurgicAI: A Hierarchical Platform for Fine-Grained Surgical Policy Learning and Benchmarking Jin Wu, Haoying Zhou, Peter Kazanzides, Adnan Munawar, Anqi Liu

TMLR 2024 Weighted Risk Invariance: Domain Generalization Under Invariant Feature Shift Gina Wong, Joshua Gleason, Rama Chellappa, Yoav Wald, Anqi Liu

AISTATS 2023 Distributionally Robust Policy Gradient for Offline Contextual Bandits Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar

ICML 2023 Double-Weighting for Covariate Shift Adaptation José I. Segovia-Martín, Santiago Mazuelas, Anqi Liu

ICML 2023 JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift Drew Prinster, Suchi Saria, Anqi Liu

IJCAI 2023 Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan

NeurIPS 2022 Ambiguous Images with Human Judgments for Robust Visual Event Classification Kate Sanders, Reno Kriz, Anqi Liu, Benjamin Van Durme

NeurIPS 2022 JAWS: Auditing Predictive Uncertainty Under Covariate Shift Drew Prinster, Anqi Liu, Suchi Saria

ICMLW 2022 Repeated Environment Inference for Invariant Learning Aayush Mishra, Anqi Liu

AISTATS 2021 Active Learning Under Label Shift Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue

AAAI 2021 Robust Fairness Under Covariate Shift Ashkan Rezaei, Anqi Liu, Omid Memarrast, Brian D. Ziebart

L4DC 2020 Robust Regression for Safe Exploration in Control Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue

ICML 2019 Active Learning for Probabilistic Structured Prediction of Cuts and Matchings Sima Behpour, Anqi Liu, Brian Ziebart

ICLR 2019 Regularized Learning for Domain Adaptation Under Label Shifts Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar

NeurIPS 2016 Adversarial Multiclass Classification: A Risk Minimization Perspective Rizal Fathony, Anqi Liu, Kaiser Asif, Brian Ziebart

AAAI 2016 Robust Classification Under Covariate Shift with Application to Active Learning Anqi Liu

AISTATS 2016 Robust Covariate Shift Regression Xiangli Chen, Mathew Monfort, Anqi Liu, Brian D. Ziebart

AAAI 2015 Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation Mathew Monfort, Anqi Liu, Brian D. Ziebart

AAAI 2015 Shift-Pessimistic Active Learning Using Robust Bias-Aware Prediction Anqi Liu, Lev Reyzin, Brian D. Ziebart

NeurIPS 2014 Robust Classification Under Sample Selection Bias Anqi Liu, Brian Ziebart