| Agnostic estimation of mean and covariance KA Lai, AB Rao, S Vempala 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS …, 2016 | 290 | 2016 |
| Solving SDD linear systems in nearly mlog1/2n time MB Cohen, R Kyng, GL Miller, JW Pachocki, R Peng, AB Rao, SC Xu Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 176 | 2014 |
| Stochastic block model and community detection in sparse graphs: A spectral algorithm with optimal rate of recovery P Chin, A Rao, V Vu Conference on Learning Theory, 391-423, 2015 | 175 | 2015 |
| Almost-linear-time algorithms for markov chains and new spectral primitives for directed graphs MB Cohen, J Kelner, J Peebles, R Peng, AB Rao, A Sidford, A Vladu Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 87 | 2017 |
| Algorithms for Lipschitz learning on graphs R Kyng, A Rao, S Sachdeva, DA Spielman Conference on Learning Theory, 1190-1223, 2015 | 74 | 2015 |
| Graph convolutional networks with motif-based attention JB Lee, RA Rossi, X Kong, S Kim, E Koh, A Rao Proceedings of the 28th ACM international conference on information and …, 2019 | 69 | 2019 |
| Sampling random spanning trees faster than matrix multiplication D Durfee, R Kyng, J Peebles, AB Rao, S Sachdeva Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 67 | 2017 |
| Solving directed Laplacian systems in nearly-linear time through sparse LU factorizations MB Cohen, J Kelner, R Kyng, J Peebles, R Peng, AB Rao, A Sidford 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS …, 2018 | 31 | 2018 |
| A structural graph representation learning framework RA Rossi, NK Ahmed, E Koh, S Kim, A Rao, Y Abbasi-Yadkori Proceedings of the 13th international conference on web search and data …, 2020 | 30 | 2020 |
| Determinant-preserving sparsification of SDDM matrices with applications to counting and sampling spanning trees D Durfee, J Peebles, R Peng, AB Rao 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 30 | 2017 |
| Approximate maximum matching in random streams A Farhadi, MT Hajiaghayi, T Mah, A Rao, RA Rossi Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 29 | 2020 |
| Heterogeneous network motifs RA Rossi, NK Ahmed, A Carranza, D Arbour, A Rao, S Kim, E Koh arXiv preprint arXiv:1901.10026, 2019 | 28 | 2019 |
| Latent network summarization: Bridging network embedding and summarization D Jin, RA Rossi, E Koh, S Kim, A Rao, D Koutra Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 24 | 2019 |
| Stochastic low-rank bandits B Kveton, C Szepesvári, A Rao, Z Wen, Y Abbasi-Yadkori, ... arXiv preprint arXiv:1712.04644, 2017 | 23 | 2017 |
| Higher-order graph convolutional networks JB Lee, RA Rossi, X Kong, S Kim, E Koh, A Rao arXiv preprint arXiv:1809.07697, 2018 | 21 | 2018 |
| Preconditioning in expectation MB Cohen, R Kyng, JW Pachocki, R Peng, A Rao arXiv preprint arXiv:1401.6236, 2014 | 17 | 2014 |
| HONE: Higher-order network embeddings RA Rossi, NK Ahmed, E Koh, S Kim, A Rao, YA Yadkori arXiv preprint arXiv:1801.09303, 2018 | 15 | 2018 |
| Coresets for classification–simplified and strengthened T Mai, C Musco, A Rao Advances in Neural Information Processing Systems 34, 11643-11654, 2021 | 10 | 2021 |
| Higher-order ranking and link prediction: From closing triangles to closing higher-order motifs RA Rossi, A Rao, S Kim, E Koh, NK Ahmed, G Wu arXiv preprint arXiv:1906.05059, 2019 | 10 | 2019 |
| Higher-order spectral clustering for heterogeneous graphs AG Carranza, RA Rossi, A Rao, E Koh arXiv preprint arXiv:1810.02959, 2018 | 10 | 2018 |
Richard PengUniversity of WaterlooVerified email at uwaterloo.ca
