54 citations · 121 across the 18 of their papers we have counts for
6 papers · 1 filter
Backtracking Improves Generation Safety
Yiming Zhang, Jianfeng Chi, Hailey Nguyen +4
Text generation has a fundamental limitation almost by definition: there is no taking back tokens that have been generated, even when they are clearly problematic. In the context o…
Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendation
Kunlin Cai, Jinghuai Zhang, Zhiqing Hong +5
As location-based services (LBS) have grown in popularity, more human mobility data has been collected. The collected data can be used to build machine learning (ML) models for LBS…
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
Xiaotian Han, Jianfeng Chi, Yu Chen +4
This paper introduces the Fair Fairness Benchmark (\textsf{FFB}), a benchmarking framework for in-processing group fairness methods. Ensuring fairness in machine learning is import…
Towards Return Parity in Markov Decision Processes
Jianfeng Chi, Jian Shen, Xinyi Dai +3
Algorithmic decisions made by machine learning models in high-stakes domains may have lasting impacts over time. However, naive applications of standard fairness criterion in stati…
Understanding and Mitigating Accuracy Disparity in Regression
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon +1
With the widespread deployment of large-scale prediction systems in high-stakes domains, e.g., face recognition, criminal justice, etc., disparity in prediction accuracy between di…
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation
Han Zhao, Jianfeng Chi, Yuan Tian +1
Crowdsourced data used in machine learning services might carry sensitive information about attributes that users do not want to share. Various methods have been proposed to minimi…