| Scalable k-means++ B Bahmani, B Moseley, A Vattani, R Kumar, S Vassilvitskii arXiv preprint arXiv:1203.6402, 2012 | 940 | 2012 |
| Filtering: a method for solving graph problems in mapreduce S Lattanzi, B Moseley, S Suri, S Vassilvitskii Proceedings of the twenty-third annual ACM symposium on Parallelism in …, 2011 | 316 | 2011 |
| Fast clustering using MapReduce A Ene, S Im, B Moseley Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 287 | 2011 |
| Fast greedy algorithms in mapreduce and streaming R Kumar, B Moseley, S Vassilvitskii, A Vattani ACM Transactions on Parallel Computing (TOPC) 2 (3), 1-22, 2015 | 272 | 2015 |
| Online scheduling via learned weights S Lattanzi, T Lavastida, B Moseley, S Vassilvitskii Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 192 | 2020 |
| On scheduling in map-reduce and flow-shops B Moseley, A Dasgupta, R Kumar, T Sarlós Proceedings of the twenty-third annual ACM symposium on Parallelism in …, 2011 | 147 | 2011 |
| Approximation bounds for hierarchical clustering: Average linkage, bisecting k-means, and local search B Moseley, JR Wang Journal of Machine Learning Research 24 (1), 1-36, 2023 | 133 | 2023 |
| Local search methods for k-means with outliers S Gupta, R Kumar, K Lu, B Moseley, S Vassilvitskii Proceedings of the VLDB Endowment 10 (7), 757-768, 2017 | 133 | 2017 |
| Fast distributed k-center clustering with outliers on massive data G Malkomes, MJ Kusner, W Chen, KQ Weinberger, B Moseley Advances in Neural Information Processing Systems 28, 2015 | 95 | 2015 |
| Efficient massively parallel methods for dynamic programming S Im, B Moseley, X Sun Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 68 | 2017 |
| Learnable and instance-robust predictions for online matching, flows and load balancing T Lavastida, B Moseley, R Ravi, C Xu arXiv preprint arXiv:2011.11743, 2020 | 59 | 2020 |
| Scheduling heterogeneous processors isn't as easy as you think A Gupta, S Im, R Krishnaswamy, B Moseley, K Pruhs Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012 | 58 | 2012 |
| Efficient nonmyopic active search S Jiang, G Malkomes, G Converse, A Shofner, B Moseley, R Garnett International Conference on Machine Learning, 1714-1723, 2017 | 57 | 2017 |
| A tutorial on amortized local competitiveness in online scheduling S Im, B Moseley, K Pruhs ACM SIGACT News 42 (2), 83-97, 2011 | 51 | 2011 |
| Functional aggregate queries with additive inequalities MA Khamis, RR Curtin, B Moseley, HQ Ngo, XL Nguyen, D Olteanu, ... ACM Transactions on Database Systems (TODS) 45 (4), 1-41, 2020 | 50 | 2020 |
| Fair hierarchical clustering S Ahmadian, A Epasto, M Knittel, R Kumar, M Mahdian, B Moseley, ... Advances in Neural Information Processing Systems 33, 21050-21060, 2020 | 50 | 2020 |
| Scheduling parallel DAG jobs online to minimize average flow time K Agrawal, J Li, K Lu, B Moseley Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete …, 2016 | 41 | 2016 |
| Online scheduling on identical machines using SRPT K Fox, B Moseley Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete …, 2011 | 41 | 2011 |
| An Online Scalable Algorithm for Minimizing ℓk-norms of Weighted Flow Time on Unrelated Machines S Im, B Moseley Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete …, 2011 | 39 | 2011 |
| Energy efficient scheduling of parallelizable jobs K Fox, S Im, B Moseley Theoretical Computer Science 726, 30-40, 2018 | 38 | 2018 |
Sungjin ImUniversity of California, Merced在 ucmerced.edu 的电子邮件经过验证
