| 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 | 104 | 2017 |
| Beyond -approximation for submodular maximization on massive data streams A Norouzi-Fard, J Tarnawski, S Mitrović, A Zandieh, A Mousavifar, ... International Conference on Machine Learning, 3829-3838, 2018 | 50 | 2018 |
| 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 | 37 | 2020 |
| 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 | 22 | 2019 |
| Dimension-independent sparse fourier transform M Kapralov, A Velingker, A Zandieh Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 20 | 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 | 15 | 2017 |
| Near input sparsity time kernel embeddings via adaptive sampling D Woodruff, A Zandieh International Conference on Machine Learning, 10324-10333, 2020 | 10 | 2020 |
| Scaling up kernel ridge regression via locality sensitive hashing A Zandieh, N Nouri, A Velingker, M Kapralov, I Razenshteyn International Conference on Artificial Intelligence and Statistics, 4088-4097, 2020 | 6* | 2020 |
| Efficiently Learning Fourier Sparse Set Functions. A Amrollahi, A Zandieh, M Kapralov, A Krause NeurIPS, 15094-15103, 2019 | 5 | 2019 |
| Sparse Fourier Transform by traversing Cooley-Tukey FFT computation graphs K Bringmann, M Kapralov, M Makarov, V Nakos, A Yagudin, A Zandieh arXiv preprint arXiv:2107.07347, 2021 | | 2021 |
| Scaling Neural Tangent Kernels via Sketching and Random Features A Zandieh, I Han, H Avron, N Shoham, C Kim, J Shin arXiv preprint arXiv:2106.07880, 2021 | | 2021 |
| Learning with Neural Tangent Kernels in Near Input Sparsity Time A Zandieh arXiv preprint arXiv:2104.00415, 2021 | | 2021 |
| Fourier Sampling in Signal Processing and Numerical Linear Algebra A Zandieh EPFL, 2020 | | 2020 |
| THL4 M Elias, GA Gluch, M Kapralov, A Kumar, M Makarov, A Mousavifar, ... | | |
Ameya Velingker | अमेय वेलिंगकरResearch Scientist, Google ResearchVerified email at google.com
