Anqi Liu

发表

Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems

Soon-Jo Chung, Yisong Yue, Anima Anandkumar, 2020, IEEE Robotics Autom. Lett..

Regularized Learning for Domain Adaptation under Label Shifts pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Fanny Yang, 2019, ICLR.

Finding Social Media Trolls: Dynamic Keyword Selection Methods for Rapidly-Evolving Online Debates pdf

Anima Anandkumar, R. Michael Alvarez, Anqi Liu, 2019, ArXiv.

Robust Covariate Shift Classification Using Multiple Feature Views

Brian D. Ziebart, Anqi Liu, Hong Wang, 2016 .

Regularized Learning for Domain Adaptation under Label Shifts pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Anqi Liu, 2019, ICLR.

Repeated Environment Inference for Invariant Learning

Anqi Liu, Aayush Mishra, 2022, 2207.12876.

Repeated Environment Inference for Invariant Learning

Anqi Liu, Aayush Mishra, 2022, ArXiv.

Ambiguous Images With Human Judgments for Robust Visual Event Classification

Benjamin Van Durme, Anqi Liu, Reno Kriz, 2022, NeurIPS.

JAWS: Auditing Predictive Uncertainty Under Covariate Shift

S. Saria, Anqi Liu, Drew Prinster, 2022, NeurIPS.

Dynamic Social Media Monitoring for Fast-Evolving Online Discussions

Anima Anandkumar, Anqi Liu, Nicholas Adams-Cohen, 2021, KDD.

Robust Covariate Shift Regression

Brian D. Ziebart, Anqi Liu, Mathew Monfort, 2016, AISTATS.

Shift-Pessimistic Active Learning Using Robust Bias-Aware Prediction

Brian D. Ziebart, Anqi Liu, Lev Reyzin, 2015, AAAI.

Consistent Robust Adversarial Prediction for General Multiclass Classification pdf

Xinhua Zhang, Brian D. Ziebart, Anqi Liu, 2018, ArXiv.

Adversarial Multiclass Classification: A Risk Minimization Perspective

Brian D. Ziebart, Anqi Liu, Rizal Fathony, 2016, NIPS.

Calibrating Zero-shot Cross-lingual (Un-)structured Predictions

Benjamin Van Durme, Anqi Liu, Zhengping Jiang, 2022, EMNLP.

Robust Fairness under Covariate Shift

Brian D. Ziebart, Anqi Liu, Omid Memarrast, 2020, AAAI.

JAWS: Predictive Inference Under Covariate Shift

S. Saria, Anqi Liu, Anqi Liu, 2022, ArXiv.

Active Learning under Label Shift

Yisong Yue, Anima Anandkumar, Anqi Liu, 2020, AISTATS.

Triply Robust Off-Policy Evaluation pdf

Yisong Yue, Anima Anandkumar, Anqi Liu, 2019, ArXiv.

Robust Regression for Safe Exploration in Control

Soon-Jo Chung, Yisong Yue, Anima Anandkumar, 2019, L4DC.

Robust Classification Under Sample Selection Bias

Brian D. Ziebart, Anqi Liu, Anqi Liu, 2014, NIPS.

Distributionally Robust Learning for Uncertainty Calibration under Domain Shift

Anima Anandkumar, Junchi Yan, Anqi Liu, 2020, 2010.05784.

Deep Distributionally Robust Learning for Calibrated Uncertainties under Domain Shift

Anima Anandkumar, Junchi Yan, Anqi Liu, 2021 .

Disentangling Observed Causal Effects from Latent Confounders using Method of Moments pdf

Hao Liu, Yisong Yue, Anima Anandkumar, 2021, ArXiv.

Modeling and Interpreting Real-world Human Risk Decision Making with Inverse Reinforcement Learning pdf

Quanying Liu, Haiyan Wu, Anqi Liu, 2019, ArXiv.

Distributionally Robust Learning for Unsupervised Domain Adaptation pdf

Yisong Yue, Anima Anandkumar, Haoxuan Wang, 2020, ArXiv.

Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach

Junchi Yan, Anima Anandkumar, Anqi Liu, 2023, IJCAI.

Active Learning for Probabilistic Structured Prediction of Cuts and Matchings

Brian D. Ziebart, Anqi Liu, Sima Behpour, 2019, ICML.

Robust Covariate Shift Prediction with General Losses and Feature Views pdf

Brian D. Ziebart, Anqi Liu, Anqi Liu, 2017, ArXiv.

Density-Softmax: Scalable and Calibrated Uncertainty Estimation under Distribution Shifts

Anqi Liu, H. Bui, 2023, 2302.06495.

Density-Softmax: Scalable and Distance-Aware Uncertainty Estimation under Distribution Shifts

Anqi Liu, H. Bui, 2023, ArXiv.

Double-Weighting for Covariate Shift Adaptation

Anqi Liu, S. Mazuelas, Jos'e I. Segovia-Mart'in, 2023, ICML.