{"total":71,"rows":[{"id":"2204.09888","title":"Fairness in Graph Mining: A Survey","created":"2022-04-21","cited_by_count":76,"area":null},{"id":"2207.10888","title":"FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification","created":"2022-07-22","cited_by_count":30,"area":null},{"id":"2202.13547","title":"RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network","created":"2022-02-28","cited_by_count":27,"area":null},{"id":"2110.09253","title":"A Sociotechnical View of Algorithmic Fairness","created":"2021-09-27","cited_by_count":24,"area":null},{"id":"2106.07239","title":"Fair Clustering Under a Bounded Cost","created":"2021-06-14","cited_by_count":21,"area":null},{"id":"2202.07170","title":"Fairness Amidst Non-IID Graph Data: A Literature Review","created":"2022-02-15","cited_by_count":20,"area":null},{"id":"2205.05396","title":"A Survey on Fairness for Machine Learning on Graphs","created":"2022-05-11","cited_by_count":20,"area":null},{"id":"2209.12396","title":"Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric","created":"2022-09-26","cited_by_count":17,"area":null},{"id":"2210.16435","title":"Scalable Spectral Clustering with Group Fairness Constraints","created":"2022-10-28","cited_by_count":16,"area":null},{"id":"2210.01953","title":"Robust Fair Clustering: A Novel Fairness Attack and Defense Framework","created":"2022-10-04","cited_by_count":13,"area":null},{"id":"2303.17743","title":"FairGen: Towards Fair Graph Generation","created":"2023-03-30","cited_by_count":12,"area":null},{"id":"2105.03714","title":"Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions","created":"2021-05-08","cited_by_count":10,"area":null},{"id":"2105.14146","title":"Deep Fair Discriminative Clustering","created":"2021-05-28","cited_by_count":10,"area":null},{"id":"2105.14172","title":"A Stochastic Alternating Balance $k$-Means Algorithm for Fair Clustering","created":"2021-05-29","cited_by_count":10,"area":null},{"id":"2106.00600","title":"Fair Clustering Using Antidote Data","created":"2021-06-01","cited_by_count":10,"area":null},{"id":"2106.02216","title":"Fairness-Aware Unsupervised Feature Selection","created":"2021-06-04","cited_by_count":10,"area":null},{"id":"2212.12040","title":"Graph Learning with Localized Neighborhood Fairness","created":"2022-12-22","cited_by_count":10,"area":null},{"id":"2305.19475","title":"Doubly Constrained Fair Clustering","created":"2023-05-31","cited_by_count":9,"area":null},{"id":"2207.03600","title":"Individual Preference Stability for Clustering","created":"2022-07-07","cited_by_count":8,"area":null},{"id":"2304.13917","title":"Proportionally Representative Clustering","created":"2023-04-27","cited_by_count":8,"area":null},{"id":"2105.03153","title":"Pairwise Fairness for Ordinal Regression","created":"2021-05-07","cited_by_count":6,"area":null},{"id":"2209.12756","title":"FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering","created":"2022-09-21","cited_by_count":6,"area":null},{"id":"2302.05788","title":"Fairness-aware Multi-view Clustering","created":"2023-02-11","cited_by_count":6,"area":null},{"id":"2109.00708","title":"Efficient Algorithms For Fair Clustering with a New Fairness Notion","created":"2021-09-02","cited_by_count":5,"area":null},{"id":"2110.12020","title":"Fairness Degrading Adversarial Attacks Against Clustering Algorithms","created":"2021-10-22","cited_by_count":5,"area":null},{"id":"2206.02667","title":"Emergent specialization from participation dynamics and multi-learner retraining","created":"2022-06-06","cited_by_count":5,"area":null},{"id":"2310.18593","title":"Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint","created":"2023-10-28","cited_by_count":5,"area":null},{"id":"2408.17396","title":"Fairness-Aware Estimation of Graphical Models","created":"2024-08-30","cited_by_count":5,"area":null},{"id":"2109.04554","title":"Feature-based Individual Fairness in k-Clustering","created":"2021-09-09","cited_by_count":4,"area":null},{"id":"2205.14198","title":"Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost","created":"2022-05-27","cited_by_count":4,"area":null},{"id":"2402.10756","title":"Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering","created":"2024-02-16","cited_by_count":4,"area":null},{"id":"2101.10905","title":"Sampling a Near Neighbor in High Dimensions -- Who is the Fairest of Them All?","created":"2021-01-26","cited_by_count":3,"area":null},{"id":"2301.03421","title":"A review of clustering models in educational data science towards fairness-aware learning","created":"2023-01-09","cited_by_count":3,"area":null},{"id":"2307.12065","title":"Spectral Normalized-Cut Graph Partitioning with Fairness Constraints","created":"2023-07-22","cited_by_count":3,"area":null},{"id":"2309.15809","title":"Fair Canonical Correlation Analysis","created":"2023-09-27","cited_by_count":3,"area":null},{"id":"2311.13766","title":"A Unified Framework for Fair Spectral Clustering With Effective Graph Learning","created":"2023-11-23","cited_by_count":3,"area":null},{"id":"2402.10762","title":"On Explaining Unfairness: An Overview","created":"2024-02-16","cited_by_count":3,"area":null},{"id":"2205.14867","title":"Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North Carolina","created":"2022-05-30","cited_by_count":1,"area":null},{"id":"2209.11762","title":"Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness","created":"2022-09-20","cited_by_count":1,"area":null},{"id":"2305.17557","title":"Fair Clustering via Hierarchical Fair-Dirichlet Process","created":"2023-05-27","cited_by_count":1,"area":null},{"id":"2306.10123","title":"Dual Node and Edge Fairness-Aware Graph Partition","created":"2023-06-16","cited_by_count":1,"area":null},{"id":"2311.01252","title":"Sanitized Clustering against Confounding Bias","created":"2023-11-02","cited_by_count":1,"area":null},{"id":"2312.09061","title":"Fair Clustering: A Causal Perspective","created":"2023-12-14","cited_by_count":1,"area":null},{"id":"2403.05669","title":"Spectral Clustering of Categorical and Mixed-type Data via Extra Graph Nodes","created":"2024-03-08","cited_by_count":1,"area":null},{"id":"2406.00599","title":"Robust Fair Clustering with Group Membership Uncertainty Sets","created":"2024-06-02","cited_by_count":1,"area":null},{"id":"2406.15960","title":"Fair Clustering: Critique, Caveats, and Future Directions","created":"2024-06-22","cited_by_count":1,"area":null},{"id":"2505.09131","title":"Fair Clustering via Alignment","created":"2025-05-14","cited_by_count":1,"area":null},{"id":"2505.22984","title":"A Computational Approach to Improving Fairness in K-means Clustering","created":"2025-05-29","cited_by_count":1,"area":null},{"id":"2508.04071","title":"Adversarial Fair Multi-View Clustering","created":"2025-08-06","cited_by_count":1,"area":null},{"id":"2512.14711","title":"Promoting Fairness in Information Access within Social Networks","created":"2025-12-08","cited_by_count":1,"area":null},{"id":"2602.08589","title":"FairRARI: A Plug and Play Framework for Fairness-Aware PageRank","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2203.02005","title":"On consistency of constrained spectral clustering under representation-aware stochastic block model","created":"2022-03-03","cited_by_count":0,"area":null},{"id":"2212.14467","title":"Cluster-level Group Representativity Fairness in $k$-means Clustering","created":"2022-12-29","cited_by_count":0,"area":null},{"id":"2305.06541","title":"Spectral Clustering on Large Datasets: When Does it Work? Theory from Continuous Clustering and Density Cheeger-Buser","created":"2023-05-11","cited_by_count":0,"area":null},{"id":"2403.16201","title":"From Discrete to Continuous: Deep Fair Clustering With Transferable Representations","created":"2024-03-24","cited_by_count":0,"area":null},{"id":"2409.02963","title":"Fair Clustering with Minimum Representation Constraints","created":"2024-09-04","cited_by_count":0,"area":null},{"id":"2505.22684","title":"Recovering Fairness Directly from Modularity: a New Way for Fair Community Partitioning","created":"2025-05-27","cited_by_count":0,"area":null},{"id":"2506.08143","title":"Accelerating Spectral Clustering under Fairness Constraints","created":"2025-06-09","cited_by_count":0,"area":null},{"id":"2506.12839","title":"Fair Bayesian Model-Based Clustering","created":"2025-06-15","cited_by_count":0,"area":null},{"id":"2508.10345","title":"Welfare-Centric Clustering","created":"2025-08-14","cited_by_count":0,"area":null},{"id":"2510.03899","title":"Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity","created":"2025-10-04","cited_by_count":0,"area":null},{"id":"2510.20220","title":"Alternatives to the Laplacian for Scalable Spectral Clustering with Group Fairness Constraints","created":"2025-10-22","cited_by_count":0,"area":null},{"id":"2510.23507","title":"A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective","created":"2025-10-27","cited_by_count":0,"area":null},{"id":"2510.27136","title":"FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance","created":"2025-10-31","cited_by_count":0,"area":null},{"id":"2511.21109","title":"Interpretable Fair Clustering","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2512.09810","title":"Incorporating Fairness in Neighborhood Graphs for Fair Spectral Clustering","created":"2025-12-10","cited_by_count":0,"area":null},{"id":"2602.18201","title":"SOMtime the World Ain$'$t Fair: Violating Fairness Using Self-Organizing Maps","created":"2026-02-20","cited_by_count":0,"area":null},{"id":"2602.21509","title":"Fair Model-based Clustering","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2607.18119","title":"COVAriance-Induced Fairness Gap Penalty for Subgroup-Fair Clustering","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2608.19381","title":"Fairness-Aware Network Embeddings: Methods, Applications, and Challenges","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2609.25811","title":"Multi-View Fair Clustering Guided by Cross-View Sensitive Information Discrepancy","created":"2026-09-22","cited_by_count":0,"area":null}],"next_cursor":null}