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Randomized Algorithms for Matrices and Massive Data Sets., and . VLDB, page 1269. ACM, (2006)Semi-supervised Eigenvectors for Locally-biased Learning., and . NIPS, page 2537-2545. (2012)Approximating Higher-Order Distances Using Random Projections., , and . UAI, page 312-321. AUAI Press, (2010)Fast Randomized Kernel Ridge Regression with Statistical Guarantees., and . NIPS, page 775-783. (2015)A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark., , , , , , , , , and 5 other author(s). IPDPS Workshops, page 1403-1412. IEEE Computer Society, (2016)Tree decompositions and social graphs., , and . Internet Mathematics, 12 (5): 315-361 (2016)Scalable Kernel K-Means Clustering with Nyström Approximation: Relative-Error Bounds., , and . J. Mach. Learn. Res., (2019)Approximating the Solution to Mixed Packing and Covering LPs in Parallel O˜(epsilon^-3) Time., , , and . ICALP, volume 55 of LIPIcs, page 52:1-52:14. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, (2016)Subspace Sampling and Relative-Error Matrix Approximation: Column-Row-Based Methods., , and . ESA, volume 4168 of Lecture Notes in Computer Science, page 304-314. Springer, (2006)Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow., , and . SEA, volume 5526 of Lecture Notes in Computer Science, page 197-208. Springer, (2009)