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ORCIDAnqi Liu 0001
Person information
- affiliation: Johns Hopkins University, Baltimore, MD, USA
Other persons with the same name
- Anqi Liu — disambiguation page
- Anqi Liu 0002
![[0000-0001-9033-6701]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-9033-6701")
— Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Haidian, Beijing, China - Anqi Liu 0003 — Cardiff University, Cardiff, UK
- Anqi Liu 0004 — Zhipu AI, Beijing, China
- Anqi Liu 0005 — Tianjin University, Tianjin, China
- Anqi Liu 0006 — Tulane University, New Orleans, LA, USA
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2020 – today
- 2026
[c21]Shiye Cao, Jiwon Moon, Yifan Xu, Anqi Liu, Chien-Ming Huang:
Reframing Conversational Design in HRI: Deliberate Design with AI Scaffolds. HRI 2026: 59-67- [i22]Shiye Cao, Jiwon Moon, Yifan Xu, Anqi Liu, Chien-Ming Huang:
Reframing Conversational Design in HRI: Deliberate Design with AI Scaffolds. CoRR abs/2601.12084 (2026) - 2025
- [c20]Drew Prinster, Xing Han, Anqi Liu, Suchi Saria:
WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales. ICML 2025 - [i21]Shiye Cao, Jiwon Moon, Amama Mahmood, Victor Nikhil Antony, Ziang Xiao, Anqi Liu, Chien-Ming Huang:
Interruption Handling for Conversational Robots. CoRR abs/2501.01568 (2025) - [i20]Drew Prinster, Xing Han, Anqi Liu, Suchi Saria:
WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales. CoRR abs/2505.04608 (2025) - [i19]Gina Wong, Drew Prinster, Suchi Saria, Rama Chellappa, Anqi Liu:
Improving Coverage in Combined Prediction Sets with Weighted p-values. CoRR abs/2505.11785 (2025) - [i18]Sara Kangaslahti, Danny Ebanks, Jean Kossaifi, Anqi Liu, R. Michael Alvarez, Animashree Anandkumar:
Analyzing Political Text at Scale with Online Tensor LDA. CoRR abs/2511.07809 (2025) - 2024
- [j3]Shiye Cao, Anqi Liu, Chien-Ming Huang:
Designing for Appropriate Reliance: The Roles of AI Uncertainty Presentation, Initial User Decision, and User Demographics in AI-Assisted Decision-Making. Proc. ACM Hum. Comput. Interact. 8(CSCW1): 1-32 (2024) - [j2]Zhaoning Li, Qiaoli Jiang, Zhengming Wu, Anqi Liu, Haiyan Wu, Miner Huang, Kai Huang, Yixuan Ku:
Towards Human-Compatible Autonomous Car: A Study of Non-Verbal Turing Test in Automated Driving With Affective Transition Modelling. IEEE Trans. Affect. Comput. 15(2): 478-492 (2024) - [c19]Drew Prinster, Samuel Don Stanton, Anqi Liu, Suchi Saria:
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). ICML 2024: 41086-41118 - [c18]Pepita Barnard, John Robert Bautista, Aidan Dakhama, Arya Farahi, Kazim Laos, Anqi Liu, Héctor D. Menéndez:
Responsible MLOps Design Methodology for an Auditing System for AI-Based Clinical Decision Support Systems. ICTSS 2024: 217-236 - [i17]Shiye Cao, Anqi Liu, Chien-Ming Huang:
Designing for Appropriate Reliance: The Roles of AI Uncertainty Presentation, Initial User Decision, and User Demographics in AI-Assisted Decision-Making. CoRR abs/2401.05612 (2024) - [i16]Drew Prinster, Samuel Stanton, Anqi Liu, Suchi Saria:
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). CoRR abs/2405.06627 (2024) - 2023
- [c17]Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar:
Distributionally Robust Policy Gradient for Offline Contextual Bandits. AISTATS 2023: 6443-6462 - [c16]Drew Prinster, Suchi Saria, Anqi Liu:
Efficient Approximate Predictive Inference Under Feedback Covariate Shift with Influence Functions. COPA 2023: 324-327 - [c15]Drew Prinster, Suchi Saria, Anqi Liu:
JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift. ICML 2023: 28167-28190 - [c14]Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan:
Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. IJCAI 2023: 1460-1469 - 2022
- [c13]Drew Prinster, Anqi Liu, Suchi Saria:
JAWS: Auditing Predictive Uncertainty Under Covariate Shift. NeurIPS 2022 - [i15]Drew Prinster, Anqi Liu, Suchi Saria:
JAWS: Predictive Inference Under Covariate Shift. CoRR abs/2207.10716 (2022) - [i14]Zhaoning Li, Qiaoli Jiang, Zhengming Wu, Anqi Liu, Haiyan Wu, Miner Huang, Kai Huang, Yixuan Ku:
Towards human-compatible autonomous car: A study of non-verbal Turing test in automated driving with affective transition modelling. CoRR abs/2212.02908 (2022) - 2021
- [j1]Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. IEEE Robotics Autom. Lett. 6(1): 389-396 (2021) - [c12]Ashkan Rezaei, Anqi Liu, Omid Memarrast, Brian D. Ziebart:
Robust Fairness Under Covariate Shift. AAAI 2021: 9419-9427 - [c11]Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue:
Active Learning under Label Shift. AISTATS 2021: 3412-3420 - [c10]Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar:
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions. KDD 2021: 3576-3584 - [i13]Anqi Liu, Hao Liu, Tongxin Li, Saeed Karimi-Bidhendi, Yisong Yue, Anima Anandkumar:
Disentangling Observed Causal Effects from Latent Confounders using Method of Moments. CoRR abs/2101.06614 (2021) - [i12]Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar:
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions. CoRR abs/2102.12596 (2021) - 2020
- [c9]Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue:
Robust Regression for Safe Exploration in Control. L4DC 2020: 608-619 - [i11]Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. CoRR abs/2005.04374 (2020) - [i10]Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue:
Active Learning under Label Shift. CoRR abs/2007.08479 (2020) - [i9]Ashkan Rezaei, Anqi Liu, Omid Memarrast, Brian D. Ziebart:
Robust Fairness under Covariate Shift. CoRR abs/2010.05166 (2020) - [i8]Haoxuan Wang, Anqi Liu, Zhiding Yu, Yisong Yue, Anima Anandkumar:
Distributionally Robust Learning for Unsupervised Domain Adaptation. CoRR abs/2010.05784 (2020)
2010 – 2019
- 2019
- [c8]Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar:
Regularized Learning for Domain Adaptation under Label Shifts. ICLR (Poster) 2019 - [c7]Sima Behpour, Anqi Liu, Brian D. Ziebart:
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings. ICML 2019: 563-572 - [i7]Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar:
Regularized Learning for Domain Adaptation under Label Shifts. CoRR abs/1903.09734 (2019) - [i6]Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue:
Robust Regression for Safe Exploration in Control. CoRR abs/1906.05819 (2019) - [i5]Anqi Liu, Maya Srikanth, Nicholas Adams-Cohen, R. Michael Alvarez, Anima Anandkumar:
Finding Social Media Trolls: Dynamic Keyword Selection Methods for Rapidly-Evolving Online Debates. CoRR abs/1911.05332 (2019) - [i4]Anqi Liu, Hao Liu, Anima Anandkumar, Yisong Yue:
Triply Robust Off-Policy Evaluation. CoRR abs/1911.05811 (2019) - 2018
- [i3]Rizal Fathony, Kaiser Asif, Anqi Liu, Mohammad Ali Bashiri, Wei Xing, Sima Behpour, Xinhua Zhang, Brian D. Ziebart:
Consistent Robust Adversarial Prediction for General Multiclass Classification. CoRR abs/1812.07526 (2018) - 2017
- [i2]Anqi Liu, Brian D. Ziebart:
Robust Covariate Shift Prediction with General Losses and Feature Views. CoRR abs/1712.10043 (2017) - [i1]Anqi Liu, Rizal Fathony, Brian D. Ziebart:
Kernel Robust Bias-Aware Prediction under Covariate Shift. CoRR abs/1712.10050 (2017) - 2016
- [c6]Xiangli Chen, Mathew Monfort, Anqi Liu, Brian D. Ziebart:
Robust Covariate Shift Regression. AISTATS 2016: 1270-1279 - [c5]Rizal Fathony, Anqi Liu, Kaiser Asif, Brian D. Ziebart:
Adversarial Multiclass Classification: A Risk Minimization Perspective. NIPS 2016: 559-567 - 2015
- [c4]Anqi Liu, Lev Reyzin, Brian D. Ziebart:
Shift-Pessimistic Active Learning Using Robust Bias-Aware Prediction. AAAI 2015: 2764-2770 - [c3]Mathew Monfort, Anqi Liu, Brian D. Ziebart:
Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation. AAAI 2015: 3672-3678 - [c2]Hong Wang, Anqi Liu, Jing Wang, Brian D. Ziebart, Clement T. Yu, Warren Shen:
Context Retrieval for Web Tables. ICTIR 2015: 251-260 - 2014
- [c1]Anqi Liu, Brian D. Ziebart:
Robust Classification Under Sample Selection Bias. NIPS 2014: 37-45
Coauthor Index
aka: Animashree Anandkumar
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