| Approaching optimality for solving SDD linear systems I Koutis, GL Miller, R Peng SIAM Journal on Computing 43 (1), 337-354, 2014 | 367 | 2014 |
| A nearly-m log n time solver for SDD linear systems I Koutis, GL Miller, R Peng Foundations of Computer Science (FOCS), 2011 IEEE 52nd Annual Symposium on …, 2011 | 321 | 2011 |
| Maximum flow and minimum-cost flow in almost-linear time L Chen, R Kyng, YP Liu, R Peng, MP Gutenberg, S Sachdeva 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 320 | 2022 |
| Uniform sampling for matrix approximation MB Cohen, YT Lee, C Musco, C Musco, R Peng, A Sidford Proceedings of the 2015 conference on innovations in theoretical computer …, 2015 | 261 | 2015 |
| 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 | 250* | 2014 |
| Efficient triangle counting in large graphs via degree-based vertex partitioning MN Kolountzakis, GL Miller, R Peng, CE Tsourakakis Internet Mathematics 8 (1-2), 161-185, 2012 | 190 | 2012 |
| Sparsified cholesky and multigrid solvers for connection laplacians R Kyng, YT Lee, R Peng, S Sachdeva, DA Spielman Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016 | 175* | 2016 |
| Fully dynamic (1+ e)-approximate matchings M Gupta, R Peng 2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 548-557, 2013 | 175 | 2013 |
| An efficient parallel solver for SDD linear systems R Peng, DA Spielman Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 174 | 2014 |
| Parallel graph decompositions using random shifts GL Miller, R Peng, SC Xu Proceedings of the twenty-fifth annual ACM symposium on Parallelism in …, 2013 | 158 | 2013 |
| Scalable large near-clique detection in large-scale networks via sampling M Mitzenmacher, J Pachocki, R Peng, C Tsourakakis, SC Xu Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 143 | 2015 |
| Approximate Undirected Maximum Flows in O(mpolylog(n)) Time R Peng Proceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete …, 2016 | 141 | 2016 |
| Iterative row sampling M Li, GL Miller, R Peng 2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 127-136, 2013 | 136 | 2013 |
| Lp Row Sampling by Lewis Weights MB Cohen, R Peng Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015 | 135 | 2015 |
| Bipartite matching in nearly-linear time on moderately dense graphs J van den Brand, YT Lee, D Nanongkai, R Peng, T Saranurak, A Sidford, ... 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 131 | 2020 |
| Partitioning well-clustered graphs: Spectral clustering works! R Peng, H Sun, L Zanetti Conference on learning theory, 1423-1455, 2015 | 129 | 2015 |
| A deterministic algorithm for balanced cut with applications to dynamic connectivity, flows, and beyond J Chuzhoy, Y Gao, J Li, D Nanongkai, R Peng, T Saranurak 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 127 | 2020 |
| 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 | 125 | 2017 |
| Fast Algorithms for ℓp-Regression D Adil, R Kyng, R Peng, S Sachdeva Journal of the ACM 71 (5), 1-45, 2024 | 101* | 2024 |
| Faster spectral sparsification and numerical algorithms for SDD matrices I Koutis, A Levin, R Peng arXiv preprint arXiv:1209.5821, 2012 | 94* | 2012 |
Gary L. MillerCarnegie Mellon UniversityVerified email at cs.cmu.edu
