| Random Fourier features for kernel ridge regression: Approximation bounds and statistical guarantees H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 41 | 2017 |
| Beyond -approximation for submodular maximization on massive data streams A Norouzi-Fard, J Tarnawski, S Mitrović, A Zandieh, A Mousavifar, ... arXiv preprint arXiv:1808.01842, 2018 | 21 | 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 | 9 | 2019 |
| An adaptive sublinear-time block sparse Fourier transform V Cevher, M Kapralov, J Scarlett, A Zandieh Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 7 | 2017 |
| Oblivious sketching of high-degree polynomial kernels TD Ahle, M Kapralov, JBT Knudsen, R Pagh, A Velingker, DP Woodruff, ... Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 4 | 2020 |
| Dimension-independent sparse Fourier transform M Kapralov, A Velingker, A Zandieh Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 4 | 2019 |
| Oblivious sketching of high-degree polynomial kernels M Kapralov, R Pagh, A Velingker, D Woodruff, A Zandieh arXiv preprint arXiv:1909.01410, 2019 | 2 | 2019 |
| Sketching high-degree polynomial kernels M Kapralov, R Pagh, A Velingker, D Woodruff, A Zandieh Manuscript, 2019 | 2 | 2019 |
| Efficiently Learning Fourier Sparse Set Functions A Amrollahi, A Zandieh, M Kapralov, A Krause Advances in Neural Information Processing Systems, 15094-15103, 2019 | 1 | 2019 |
| Scaling up Kernel Ridge Regression via Locality Sensitive Hashing M Kapralov, N Nouri, I Razenshteyn, A Velingker, A Zandieh arXiv preprint arXiv:2003.09756, 2020 | | 2020 |
Ameya VelingkerCollaborateur Scientifique (Research Scientist)Verified email at epfl.ch
