no code implementations • 18 Jul 2023 • Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
While the presence of labeling bias has been discussed conceptually, there is a lack of methodologies to address this problem.
no code implementations • 15 Jul 2022 • Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
We then empirically show that, when overlooking label bias, collecting more data can aggravate bias, and imposing fairness constraints that rely on the observed labels in the data collection process may not address the problem.
no code implementations • 15 May 2022 • Yunyi Li, Yiqiu Jiang, Hengmin Zhang, Jianxun Liu, Xiangling Ding, Guan Gui
In this paper, we develop a ${{L_ {{1/2}}}} $-regularized nonlocal self-similarity (NSS) denoiser for CT reconstruction problem, which integrates low-rank approximation with group sparse coding (GSC) framework.
no code implementations • 20 Nov 2021 • Yunyi Li, Pengpeng Zhao, Guanfeng Liu, Yanchi Liu, Victor S. Sheng, Jiajie Xu, Xiaofang Zhou
In this paper, we propose an Edge-Enhanced Global Disentangled Graph Neural Network (EGD-GNN) model to capture the relation information between items for global item representation and local user intention learning.
no code implementations • 6 May 2021 • Tong Wang, Jingyi Yang, Yunyi Li, Boxiang Wang
We propose Partially Interpretable Estimators (PIE) which attribute a prediction to individual features via an interpretable model, while a (possibly) small part of the PIE prediction is attributed to the interaction of features via a black-box model, with the goal to boost the predictive performance while maintaining interpretability.
no code implementations • 18 Nov 2019 • Yunyi Li, Li Liu, Yu Zhao, Xiefeng Cheng, Guan Gui
The popular L_2-norm and M-estimator are employed for standard image CS and robust CS problem to fit the data respectively.
no code implementations • 10 Jul 2019 • Yunyi Li, Guan Gui, Xiefeng Cheng
Recently, low-rank matrix recovery theory has been emerging as a significant progress for various image processing problems.
no code implementations • 23 Mar 2019 • Yunyi Li, Fei Dai, Yu Zhao, Xiefeng Cheng, Guan Gui
Group-prior based regularization method has led to great successes in various image processing tasks, which can usually be considered as a low-rank matrix minimization problem.
Image and Video Processing
no code implementations • 13 Dec 2018 • Yunyi Li, Tong Wang
Our goal is to predict the location of the next crime in a crime series, based on the identified previous offenses in the series.