2 citations · 2 across the 6 of their papers we have counts for
6 papers
Recovering Fairness Directly from Modularity: a New Way for Fair Community Partitioning
Yufeng Wang, Yiguang Bai, Tianqing Zhu +2
Community partitioning is crucial in network analysis, with modularity optimization being the prevailing technique. However, traditional modularity-based methods often overlook fai…
Submodular Participatory Budgeting
Jing Yuan, Shaojie Tang
Participatory budgeting refers to the practice of allocating public resources by collecting and aggregating individual preferences. Most existing studies in this field often assume…
Beyond Submodularity: A Unified Framework of Randomized Set Selection with Group Fairness Constraints
Shaojie Tang, Jing Yuan
Machine learning algorithms play an important role in a variety of important decision-making processes, including targeted advertisement displays, home loan approvals, and criminal…
Achieving Long-term Fairness in Submodular Maximization through Randomization
Shaojie Tang, Jing Yuan, Twumasi Mensah-Boateng
Submodular function optimization has numerous applications in machine learning and data analysis, including data summarization which aims to identify a concise and diverse set of d…
Group Fairness in Non-monotone Submodular Maximization
Jing Yuan, Shaojie Tang
Maximizing a submodular function has a wide range of applications in machine learning and data mining. One such application is data summarization whose goal is to select a small se…
Streaming Adaptive Submodular Maximization
Shaojie Tang, Jing Yuan
Many sequential decision making problems can be formulated as an adaptive submodular maximization problem. However, most of existing studies in this field focus on pool-based setti…