PateGAIL++: Utility Optimized Private Trajectory Generation with Imitation Learning

ICLROral2026

Authors
Yingjie Ma, Bijal Bharadva, Xin Zhang, Joann Qiongna Chen
Venue
ICLR 2026
Track
Oral

TL;DR

Human mobility trajectory data supports a wide range of applications, including urban planning, intelligent transportation systems, and public safety monitoring. However, large-scale, high-quality mobility datasets are difficult to obtain due to privacy concerns.

Opening excerpt from the authors’ abstract. source

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Topics

imitation learning planning dataset privacy safety

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