Shashanka Ubaru
Shashanka Ubaru
IBM Research
Verifierad e-postadress på umn.edu - Startsida
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Fast Estimation of via Stochastic Lanczos Quadrature
S Ubaru, J Chen, Y Saad
SIAM Journal on Matrix Analysis and Applications 38 (4), 1075-1099, 2017
652017
Fast methods for estimating the numerical rank of large matrices
S Ubaru, Y Saad
International Conference on Machine Learning, 468-477, 2016
242016
Improving the incoherence of a learned dictionary via rank shrinkage
S Ubaru, AK Seghouane, Y Saad
Neural computation 29 (1), 263-285, 2017
172017
Spectrum approximation beyond fast matrix multiplication: Algorithms and hardness
C Musco, P Netrapalli, A Sidford, S Ubaru, DP Woodruff
arXiv preprint arXiv:1704.04163, 2017
142017
Formation enthalpies for transition metal alloys using machine learning
S Ubaru, A Międlar, Y Saad, JR Chelikowsky
Physical Review B 95 (21), 214102, 2017
122017
Union of intersections (uoi) for interpretable data driven discovery and prediction
K Bouchard, A Bujan, F Roosta, S Ubaru, M Prabhat, A Snijders, JH Mao, ...
Advances in Neural Information Processing Systems, 1078-1086, 2017
122017
Multilabel classification with group testing and codes
S Ubaru, A Mazumdar
International Conference on Machine Learning, 3492-3501, 2017
112017
Fast estimation of approximate matrix ranks using spectral densities
S Ubaru, Y Saad, AK Seghouane
Neural computation 29 (5), 1317-1351, 2017
112017
Low rank approximation and decomposition of large matrices using error correcting codes
S Ubaru, A Mazumdar, Y Saad
IEEE Transactions on Information Theory 63 (9), 5544-5558, 2017
92017
Low rank approximation using error correcting coding matrices
S Ubaru, A Mazumdar, Y Saad
International Conference on Machine Learning, 702-710, 2015
92015
Sampling and multilevel coarsening algorithms for fast matrix approximations
S Ubaru, Y Saad
Numerical Linear Algebra with Applications 26 (3), e2234, 2019
72019
UoI-NMF cluster: a robust nonnegative matrix factorization algorithm for improved parts-based decomposition and reconstruction of noisy data
S Ubaru, K Wu, KE Bouchard
2017 16th IEEE International Conference on Machine Learning and Applications …, 2017
72017
Group testing schemes from low-weight codewords of BCH codes
S Ubaru, A Mazumdar, A Barg
2016 IEEE International Symposium on Information Theory (ISIT), 2863-2867, 2016
62016
Spectrum-adapted polynomial approximation for matrix functions
L Fan, DI Shuman, S Ubaru, Y Saad
arXiv preprint arXiv:1808.09506, 2018
32018
Applications of trace estimation techniques
S Ubaru, Y Saad
International Conference on High Performance Computing in Science and …, 2017
32017
Find the dimension that counts: Fast dimension estimation and Krylov PCA
S Ubaru, AK Seghouane, Y Saad
Proceedings of the 2019 SIAM International Conference on Data Mining, 720-728, 2019
12019
Run procrustes, run! on the convergence of accelerated procrustes flow
A Kyrillidis, S Ubaru, G Kollias, K Bouchard
arXiv preprint arXiv:1806.00534, 2018
12018
Projection techniques to update the truncated SVD of evolving matrices
V Kalantzis, G Kollias, S Ubaru, AN Nikolakopoulos, L Horesh, ...
arXiv preprint arXiv:2010.06392, 2020
2020
Dynamic graph based epidemiological model for COVID-19 contact tracing data analysis and optimal testing prescription
S Ubaru, L Horesh, G Cohen
arXiv preprint arXiv:2009.04971, 2020
2020
Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping
S Ubaru, S Dash, A Mazumdar, O Gunluk
arXiv preprint arXiv:2006.14084, 2020
2020
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Artiklar 1–20