| Randomized Algorithms for Estimating the Trace of an Implicit Symmetric Positive Semi-definite Matrix H Avron, S Toledo Journal of the ACM (JACM) 58 (2), 8, 2011 | 427 | 2011 |
| Blendenpik: Supercharging LAPACK's Least-Squares Solver H Avron, P Maymounkov, S Toledo SIAM J. Scientific Computing (SISC) 32 (3), 1217--1236, 2010 | 309 | 2010 |
| ℓ 1-Sparse Reconstruction of Sharp Point Set Surfaces H Avron, A Sharf, C Greif, D Cohen-Or ACM Transactions on Graphics (TOG) 29 (5), 135, 2010 | 239 | 2010 |
| Random Fourier features for kernel ridge regression: Approximation bounds and statistical guarantees H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh International conference on machine learning, 253-262, 2017 | 192 | 2017 |
| Kernel Methods Match Deep Neural Networks on TIMIT PS Huang, H Avron, TN Sainath, V Sindhwani, B Ramabhadran 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 170 | 2014 |
| Faster kernel ridge regression using sketching and preconditioning H Avron, KL Clarkson, DP Woodruff SIAM Journal on Matrix Analysis and Applications 38 (4), 1116-1138, 2017 | 147 | 2017 |
| Quasi-Monte Carlo feature maps for shift-invariant kernels J Yang, V Sindhwani, H Avron, M Mahoney International Conference on Machine Learning, 485-493, 2014 | 130 | 2014 |
| Faster Subset Selection for Matrices and Applications H Avron, C Boutsidis SIAM Journal on Matrix Analysis and Applications (SIMAX) 34 (4), 1464-1499, 2013 | 121 | 2013 |
| Subspace embeddings for the polynomial kernel H Avron, H Nguyen, D Woodruff Advances in Neural Information Processing Systems (NIPS), 2258-2266, 2014 | 119 | 2014 |
| Revisiting Asynchronous Linear Solvers: Provable Convergence Rate Through Randomization H Avron, A Druinsky, A Gupta Journal of the ACM (JACM) 62 (6), 51:1--51:27, 2015 | 110 | 2015 |
| Counting Triangles in Large Graphs Using Randomized Matrix Trace Estimation H Avron Large-scale Data Mining: Theory and Applications (KDD 2010 Workshop), 2010 | 104 | 2010 |
| Tensor-tensor algebra for optimal representation and compression of multiway data ME Kilmer, L Horesh, H Avron, E Newman Proceedings of the National Academy of Sciences 118 (28), e2015851118, 2021 | 100* | 2021 |
| Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels H Avron, V Sindhwani, J Yang, MW Mahoney Journal of Machine Learning Research (JMLR) 17 (120), 1-38, 2016 | 95 | 2016 |
| Approximating spectral sums of large-scale matrices using stochastic Chebyshev approximations I Han, D Malioutov, H Avron, J Shin SIAM Journal on Scientific Computing 39 (4), A1558-A1585, 2017 | 87 | 2017 |
| Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization H Avron, S Kale, S Kasiviswanathan, V Sindhwani Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012 | 77 | 2012 |
| Sharper bounds for regularized data fitting H Avron, KL Clarkson, DP Woodruff arXiv preprint arXiv:1611.03225, 2016 | 71* | 2016 |
| Efficient Dimensionality Reduction for Canonical Correlation Analysis H Avron, C Boutsidis, S Toledo, A Zouzias SIAM Journal on Scientific Computing (SISC) 36 (5), S111-131, 2014 | 67 | 2014 |
| Random Laplace Feature Maps for Semigroup Kernels on Histograms J Yang, V Sindhwani, Q Fan, H Avron, MW Mahoney Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 64 | 2014 |
| Stable tensor neural networks for rapid deep learning E Newman, L Horesh, H Avron, M Kilmer arXiv preprint arXiv:1811.06569, 2018 | 48 | 2018 |
| A universal sampling method for reconstructing signals with simple fourier transforms H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 40 | 2019 |
Lior HoreshIBM TJ Watson Research Center | Columbia UniversityVerified email at us.ibm.com
