Shashanka Ubaru
Shashanka Ubaru
IBM Research
Verified email at - Homepage
TitleCited byYear
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
Fast methods for estimating the numerical rank of large matrices
S Ubaru, Y Saad
International Conference on Machine Learning, 468-477, 2016
Improving the incoherence of a learned dictionary via rank shrinkage
S Ubaru, AK Seghouane, Y Saad
Neural computation 29 (1), 263-285, 2017
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
Fast estimation of approximate matrix ranks using spectral densities
S Ubaru, Y Saad, AK Seghouane
Neural Computation 29 (5), 1317-1351, 2017
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
Formation enthalpies for transition metal alloys using machine learning
S Ubaru, A Międlar, Y Saad, JR Chelikowsky
Physical Review B 95 (21), 214102, 2017
Low rank approximation using error correcting coding matrices
S Ubaru, A Mazumdar, Y Saad
International Conference on Machine Learning, 702-710, 2015
Multilabel classification with group testing and codes
S Ubaru, A Mazumdar
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Union of intersections (uoi) for interpretable data driven discovery and prediction
K Bouchard, A Bujan, F Roosta-Khorasani, S Ubaru, M Prabhat, ...
Advances in Neural Information Processing Systems, 1078-1086, 2017
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
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
Sampling and multilevel coarsening algorithms for fast matrix approximations
S Ubaru, Y Saad
Numerical Linear Algebra with Applications 26 (3), e2234, 2019
Spectrum-adapted Polynomial Approximation for Matrix Functions
L Fan, DI Shuman, S Ubaru, Y Saad
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
Run Procrustes, Run! On the convergence of accelerated Procrustes Flow
A Kyrillidis, S Ubaru, G Kollias, K Bouchard
arXiv preprint arXiv:1806.00534, 2018
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
Provably convergent acceleration in factored gradient descent with applications in matrix sensing
T Ajayi, D Mildebrath, A Kyrillidis, S Ubaru, G Kollias, K Bouchard
arXiv preprint arXiv:1806.00534, 2018
Algorithmic advances in learning from large dimensional matrices and scientific data
S Ubaru
Applications of trace estimation techniques
S Ubaru, Y Saad
International Conference on High Performance Computing in Science and …, 2017
Randomized techniques for matrix decomposition and estimating the approximate rank of a matrix
S Ubaru
The system can't perform the operation now. Try again later.
Articles 1–20