| Iterative Refinement for ℓp-norm Regression D Adil, R Kyng, R Peng, S Sachdeva Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 78 | 2019 |
| Fast, provably convergent irls algorithm for p-norm linear regression D Adil, R Peng, S Sachdeva Advances in Neural Information Processing Systems 32, 2019 | 43 | 2019 |
| Faster p-norm minimizing flows, via smoothed q-norm problems D Adil, S Sachdeva Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 33 | 2020 |
| Parameterized algorithms for stable matching with ties and incomplete lists D Adil, S Gupta, S Roy, S Saurabh, M Zehavi Theoretical Computer Science 723, 1-10, 2018 | 25 | 2018 |
| Optimal methods for higher-order smooth monotone variational inequalities D Adil, B Bullins, A Jambulapati, S Sachdeva arXiv preprint arXiv:2205.06167, 2022 | 22* | 2022 |
| Almost-linear-time Weighted -norm Solvers in Slightly Dense Graphs via Sparsification D Adil, B Bullins, R Kyng, S Sachdeva arXiv preprint arXiv:2102.06977, 2021 | 18 | 2021 |
| Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization D Adil, B Bullins, S Sachdeva Advances in Neural Information Processing Systems 34, 19122-19133, 2021 | 8 | 2021 |
| Fast Algorithms for ℓp-Regression D Adil, R Kyng, R Peng, S Sachdeva Journal of the ACM 71 (5), 1-45, 2024 | 7* | 2024 |
| Decremental -Approximate Maximum Eigenvector: Dynamic Power Method D Adil, T Saranurak arXiv preprint arXiv:2402.17929, 2024 | 2 | 2024 |
| Convex optimization with -norm oracles D Adil, B Bullins, A Jambulapati, A Sidford arXiv preprint arXiv:2410.24158, 2024 | 1 | 2024 |
| Acceleration Meets Inverse Maintenance: Faster -Regression D Adil, S Jiang, R Kyng arXiv preprint arXiv:2409.20030, 2024 | | 2024 |
| Fast Algorithms for ℓp-Regression and Other Problems D Adil University of Toronto (Canada), 2022 | | 2022 |
| Matching Under Preferences D Adil | | 2017 |
Sushant SachdevaUToronto, Associate Professor. Vector Institute AffiliateVerified email at cs.toronto.edu
