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EigenRec: generalizing PureSVD for effective and efficient top-N recommendations., , , and . Knowl. Inf. Syst., 58 (1): 59-81 (2019)Projection techniques to update the truncated SVD of evolving matrices., , , , , and . CoRR, (2020)Estimating the Trace of the Matrix Inverse by Interpolating from the Diagonal of an Approximate Inverse., , , , and . CoRR, (2015)Fast randomized non-Hermitian eigensolver based on rational filtering and matrix partitioning., , and . CoRR, (2021)Beyond Automated Multilevel Substructuring: Domain Decomposition with Rational Filtering., , and . SIAM J. Sci. Comput., 40 (4): C477-C502 (2018)EIGENREC: An Efficient and Scalable Latent Factor Family for Top-N Recommendation., , and . CoRR, (2015)Quantum Graph Transformers., , , and . ICASSP, page 1-5. IEEE, (2023)Factored Proximity Models for Top-N Recommendations., , , and . ICBK, page 80-87. IEEE Computer Society, (2017)Accelerating data uncertainty quantification by solving linear systems with multiple right-hand sides., , , and . Numer. Algorithms, 62 (4): 637-653 (2013)parGeMSLR: A Parallel Multilevel Schur Complement Low-Rank Preconditioning and Solution Package for General Sparse Matrices., , , , , and . CoRR, (2022)