| 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 | 224 | 2011 |
| Blendenpik: Supercharging LAPACK's Least-Squares Solver H Avron, P Maymounkov, S Toledo SIAM J. Scientific Computing (SISC) 32 (3), 1217--1236, 2010 | 203 | 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 | 143 | 2010 |
| 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 | 130 | 2014 |
| 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 | 95 | 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 | 93 | 2013 |
| 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 | 92 | 2015 |
| Counting Triangles in Large Graphs Using Randomized Matrix Trace Estimation H Avron Large-scale Data Mining: Theory and Applications (KDD 2010 Workshop), 2010 | 78 | 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 | 72 | 2017 |
| Subspace embeddings for the polynomial kernel H Avron, H Nguyen, D Woodruff Advances in Neural Information Processing Systems (NIPS), 2258-2266, 2014 | 69 | 2014 |
| 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 | 66 | 2012 |
| 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 | 60 | 2017 |
| 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 | 54 | 2014 |
| 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 | 52 | 2014 |
| 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 | 49 | 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 | 46 | 2017 |
| PFunc: modern task parallelism for modern high performance computing P Kambadur, A Gupta, A Ghoting, H Avron, A Lumsdaine International Conference for High Performance Computing, Networking, Storage …, 2009 | 40 | 2009 |
| Sharper bounds for regularized data fitting H Avron, KL Clarkson, DP Woodruff arXiv preprint arXiv:1611.03225, 2016 | 34* | 2016 |
| Using perturbed QR factorizations to solve linear least-squares problems H Avron, E Ng, S Toledo SIAM J. Matrix Analysis Applications (SIMAX) 31 (2), 674--693, 2009 | 28 | 2009 |
| High-performance kernel machines with implicit distributed optimization and randomization H Avron, V Sindhwani Technometrics 58 (3), 341-349, 2016 | 26* | 2016 |
Sivan ToledoProfessor and Head, Blavatnik School of Computer Science, Tel Aviv UniversityVerified email at tau.ac.il
