2 citations · 2 across the 1 of their papers we have counts for
6 papers
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…
Intent Classification and Slot Filling for Privacy Policies
Wasi Uddin Ahmad, Jianfeng Chi, Tu Le +3
Understanding privacy policies is crucial for users as it empowers them to learn about the information that matters to them. Sentences written in a privacy policy document explain…
PolicyQA: A Reading Comprehension Dataset for Privacy Policies
Wasi Uddin Ahmad, Jianfeng Chi, Yuan Tian +1
Privacy policy documents are long and verbose. A question answering (QA) system can assist users in finding the information that is relevant and important to them. Prior studies in…
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries
Fnu Suya, Jianfeng Chi, David Evans +1
We study adversarial examples in a black-box setting where the adversary only has API access to the target model and each query is expensive. Prior work on black-box adversarial ex…
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…
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase
Jianfeng Chi, Emmanuel Owusu, Xuwang Yin +4
We present a practical method for protecting data during the inference phase of deep learning based on bipartite topology threat modeling and an interactive adversarial deep networ…