Terrance Liu

According to our database, Terrance Liu authored at least 15 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2025

Optimizing Canaries for Privacy Auditing with Metagradient Descent.

Matteo Boglioni, Terrance Liu, Andrew Ilyas, Zhiwei Steven Wu

CoRR, July, 2025

Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference.

Terrance Liu, Matteo Boglioni, Yiwei Fu, Shengyuan Hu, Pratiksha Thaker, Zhiwei Steven Wu

CoRR, June, 2025

Breaking the Gold Standard: Extracting Forgotten Data under Exact Unlearning in Large Language Models.

Xiaoyu Wu, Yifei Pang, Terrance Liu, Zhiwei Steven Wu

CoRR, May, 2025

Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies.

Terrance Liu, Shuyi Wang, Daniel Preotiuc-Pietro, Yash Chandarana, Chirag Gupta

CoRR, May, 2025

Generate-then-Verify: Reconstructing Data from Limited Published Statistics.

Terrance Liu, Eileen Xiao, Pratiksha Thaker, Adam Smith, Zhiwei Steven Wu

CoRR, April, 2025

Winning the MIDST Challenge: New Membership Inference Attacks on Diffusion Models for Tabular Data Synthesis.

Xiaoyu Wu, Yifei Pang, Terrance Liu, Zhiwei Steven Wu

CoRR, March, 2025

Multi-group Uncertainty Quantification for Long-form Text Generation.

Terrance Liu, Steven Wu

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

2023

Generating Private Synthetic Data with Genetic Algorithms.

Terrance Liu, Jingwu Tang, Giuseppe Vietri, Steven Wu

Proceedings of the International Conference on Machine Learning, 2023

2022

Confidence-Ranked Reconstruction of Census Microdata from Published Statistics.

Travis Dick, Cynthia Dwork, Michael Kearns, Terrance Liu, Aaron Roth, Giuseppe Vietri, Zhiwei Steven Wu

CoRR, 2022

Private Synthetic Data with Hierarchical Structure.

Terrance Liu, Zhiwei Steven Wu

CoRR, 2022

2021

Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods.

Terrance Liu, Giuseppe Vietri, Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Leveraging Public Data for Practical Private Query Release.

Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data.

Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nicholas B. Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study.

Terrance Liu, Paul Pu Liang, Michal Muszynski, Ryo Ishii, David Brent, Randy Auerbach, Nicholas B. Allen, Louis-Philippe Morency

CoRR, 2020

Think Locally, Act Globally: Federated Learning with Local and Global Representations.

Paul Pu Liang, Terrance Liu, Liu Ziyin, Ruslan Salakhutdinov, Louis-Philippe Morency

CoRR, 2020