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Optimizing Batch Linear Queries under Exact and Approximate Differential Privacy., , , , , and . CoRR, (2015)Millionaire: a hint-guided approach for crowdsourcing., , , , , , and . Mach. Learn., 108 (5): 831-858 (2019)GlassDB: Practical Verifiable Ledger Database Through Transparency., , , , , , and . CoRR, (2022)ANGEL: Enhancing the Utility of Generalization for Privacy Preserving Publication., , , , and . IEEE Trans. Knowl. Data Eng., 21 (7): 1073-1087 (2009)Efficient and Effective Algorithms for Clustering Uncertain Graphs., , , , , , and . Proc. VLDB Endow., 12 (6): 667-680 (2019)Multidimensional reverse k NN search., , , and . VLDB J., 16 (3): 293-316 (2007)LSCALE: Latent Space Clustering-Based Active Learning for Node Classification., , , , and . ECML/PKDD (1), volume 13713 of Lecture Notes in Computer Science, page 55-70. Springer, (2022)Node-wise Diffusion for Scalable Graph Learning., , , , and . WWW, page 1723-1733. ACM, (2023)iReduct: differential privacy with reduced relative errors., , , and . SIGMOD Conference, page 229-240. ACM, (2011)GBLENDER: towards blending visual query formulation and query processing in graph databases., , , , and . SIGMOD Conference, page 111-122. ACM, (2010)