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High-precision Estimation of Random Walks in Small Space.

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Learning Some Popular Gaussian Graphical Models without Condition Number Bounds., , , и . CoRR, (2019)Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations., , , , , , и . FOCS, стр. 898-909. IEEE Computer Society, (2018)Spectral Sparsification in the Semi-Streaming Setting., и . STACS, том 9 из LIPIcs, стр. 440-451. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2011)Multiple description vector quantization with a coarse lattice., , и . IEEE Trans. Inf. Theory, 48 (3): 781-788 (2002)Topology discovery of sparse random graphs with few participants., , и . SIGMETRICS, стр. 293-304. ACM, (2011)High-precision Estimation of Random Walks in Small Space., , , , , и . CoRR, (2019)High-precision Estimation of Random Walks in Small Space., , , , , и . FOCS, стр. 1295-1306. IEEE, (2020)Learning Some Popular Gaussian Graphical Models without Condition Number Bounds., , , и . NeurIPS, (2020)Semi-Random Sparse Recovery in Nearly-Linear Time., , , , и . COLT, том 195 из Proceedings of Machine Learning Research, стр. 2352-2398. PMLR, (2023)Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales., , , , , и . COLT, том 178 из Proceedings of Machine Learning Research, стр. 2431-2540. PMLR, (2022)