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Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings., , , , and . CoRR, (2024)Laplacian Eigenmaps From Sparse, Noisy Similarity Measurements., and . IEEE Trans. Signal Process., 65 (8): 1988-2003 (2017)An evaluation of graph clustering methods for unsupervised term discovery., , and . INTERSPEECH, page 3209-3213. ISCA, (2015)On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Maximum Likelihood Estimation and Graph Matching., , , and . J. Mach. Learn. Res., (2016)A Central Limit Theorem for an Omnibus Embedding of Multiple Random Dot Product Graphs., , , , and . ICDM Workshops, page 964-967. IEEE Computer Society, (2017)Vertex Nomination, Consistent Estimation, and Adversarial Modification., , , , , and . CoRR, (2019)Adversarial contamination of networks in the setting of vertex nomination: a new trimming method., , and . CoRR, (2022)Statistical Inference on Random Dot Product Graphs: a Survey., , , , , , , , , and . J. Mach. Learn. Res., (2017)Sharp Threshold Asymptotics for the Emergence of Additive Bases., , , and . Integers, (2013)Leveraging semantically similar queries for ranking via combining representations., , , , , , , , , and 1 other author(s). CoRR, (2021)