| Edit distance cannot be computed in strongly subquadratic time (unless SETH is false) A Backurs, P Indyk Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015 | 449 | 2015 |
| Tight hardness results for LCS and other sequence similarity measures A Abboud, A Backurs, VV Williams 2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 59-78, 2015 | 329* | 2015 |
| Differentially private fine-tuning of language models D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ... arXiv preprint arXiv:2110.06500, 2021 | 277 | 2021 |
| Scalable fair clustering A Backurs, P Indyk, K Onak, B Schieber, A Vakilian, T Wagner International Conference on Machine Learning, 405-413, 2019 | 244 | 2019 |
| If the current clique algorithms are optimal, so is Valiant's parser A Abboud, A Backurs, VV Williams SIAM Journal on Computing 47 (6), 2527-2555, 2018 | 142 | 2018 |
| Which regular expression patterns are hard to match? A Backurs, P Indyk 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS …, 2016 | 111 | 2016 |
| Space and time efficient kernel density estimation in high dimensions A Backurs, P Indyk, T Wagner Advances in neural information processing systems 32, 2019 | 73 | 2019 |
| Towards tight approximation bounds for graph diameter and eccentricities A Backurs, L Roditty, G Segal, VV Williams, N Wein Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 71 | 2018 |
| Scalable nearest neighbor search for optimal transport A Backurs, Y Dong, P Indyk, I Razenshteyn, T Wagner International Conference on machine learning, 497-506, 2020 | 63 | 2020 |
| Unveiling transformers with lego: a synthetic reasoning task Y Zhang, A Backurs, S Bubeck, R Eldan, S Gunasekar, T Wagner arXiv preprint arXiv:2206.04301, 2022 | 59 | 2022 |
| Subtree isomorphism revisited A Abboud, A Backurs, TD Hansen, V Vassilevska Williams, O Zamir ACM Transactions on Algorithms (TALG) 14 (3), 1-23, 2018 | 58 | 2018 |
| Tight hardness results for maximum weight rectangles A Backurs, N Dikkala, C Tzamos arXiv preprint arXiv:1602.05837, 2016 | 57 | 2016 |
| Improving viterbi is hard: Better runtimes imply faster clique algorithms A Backurs, C Tzamos International Conference on Machine Learning, 311-321, 2017 | 54 | 2017 |
| On the fine-grained complexity of empirical risk minimization: Kernel methods and neural networks A Backurs, P Indyk, L Schmidt Advances in Neural Information Processing Systems 30, 2017 | 49 | 2017 |
| Search by quantum walks on two-dimensional grid without amplitude amplification A Ambainis, A Bačkurs, N Nahimovs, R Ozols, A Rivosh Conference on Quantum Computation, Communication, and Cryptography, 87-97, 2012 | 48 | 2012 |
| Fine-grained complexity of analyzing compressed data: Quantifying improvements over decompress-and-solve A Abboud, A Backurs, K Bringmann, M Künnemann 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 47 | 2017 |
| Better approximations for tree sparsity in nearly-linear time A Backurs, P Indyk, L Schmidt Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 40 | 2017 |
| Exploring the limits of differentially private deep learning with group-wise clipping J He, X Li, D Yu, H Zhang, J Kulkarni, YT Lee, A Backurs, N Yu, J Bian arXiv preprint arXiv:2212.01539, 2022 | 39 | 2022 |
| Towards hardness of approximation for polynomial time problems A Abboud, A Backurs 8th Innovations in Theoretical Computer Science Conference (ITCS 2017), 2017 | 39 | 2017 |
| Efficient density evaluation for smooth kernels A Backurs, M Charikar, P Indyk, P Siminelakis 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS …, 2018 | 37 | 2018 |
