| 'Beating the news' with EMBERS: forecasting civil unrest using open source indicators N Ramakrishnan, P Butler, S Muthiah, N Self, R Khandpur, P Saraf, ... Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 275 | 2014 |
| An Improved Approximation for k-Median and Positive Correlation in Budgeted Optimization J Byrka, T Pensyl, B Rybicki, A Srinivasan, K Trinh ACM Transactions on Algorithms (TALG) 13 (2), 1-31, 2017 | 266 | 2017 |
| A lottery model for center-type problems with outliers DG Harris, T Pensyl, A Srinivasan, K Trinh ACM Transactions on Algorithms (TALG) 15 (3), 1-25, 2019 | 30 | 2019 |
| An improved approximation algorithm for knapsack median using sparsification J Byrka, T Pensyl, B Rybicki, J Spoerhase, A Srinivasan, K Trinh Algorithmica 80, 1093-1114, 2018 | 18 | 2018 |
| Approximation algorithms for stochastic clustering D Harris, S Li, A Srinivasan, K Trinh, T Pensyl Advances in Neural Information Processing Systems 31, 2018 | 17 | 2018 |
| A lottery model for center-type problems with outliers DG Harris, T Pensyl, A Srinivasan, K Trinh arXiv preprint arXiv:1710.00287, 2017 | 10 | 2017 |
| Symmetric randomized dependent rounding DG Harris, T Pensyl, A Srinivasan, K Trinh CoRR, abs/1709.06995, 2017 | 5 | 2017 |
| Fairness in resource allocation and slowed-down dependent rounding DG Harris, T Pensyl, A Srinivasan, K Trinh arXiv preprint arXiv:1704.06528, 2017 | 3 | 2017 |
| An Approximation Approach for a Real–World Variant of Vehicle Routing Problem K Trinh, N Dang, T Dinh New Challenges for Intelligent Information and Database Systems, 87-96, 2011 | 3 | 2011 |
| Improved Bi-point Rounding Algorithms and a Golden Barrier for k-Median KN Gowda, T Pensyl, A Srinivasan, K Trinh Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023 | 2 | 2023 |
| Weighted Distillation with Unlabeled Examples F Iliopoulos, V Kontonis, C Baykal, G Menghani, K Trinh, E Vee arXiv preprint arXiv:2210.06711, 2022 | 2 | 2022 |
| Dependent randomized rounding for clustering and partition systems with knapsack constraints DG Harris, T Pensyl, A Srinivasan, K Trinh The Journal of Machine Learning Research 23 (1), 3494-3534, 2022 | 2 | 2022 |
| A stochastic optimization method for solving the machine–part cell formation problem K Trinh, J Ferland, T Dinh Advanced Intelligent Computing: 7th International Conference, ICIC 2011 …, 2012 | 2 | 2012 |
| Dependent rounding for knapsack/partition constraints and facility location DG Harris, T Pensyl, A Srinivasan, K Trinh arXiv preprint arXiv:1709.06995, 2017 | 1 | 2017 |
| SLaM: Student-Label Mixing for Semi-Supervised Knowledge Distillation V Kontonis, F Iliopoulos, K Trinh, C Baykal, G Menghani, E Vee arXiv preprint arXiv:2302.03806, 2023 | | 2023 |
| Robust Active Distillation C Baykal, K Trinh, F Iliopoulos, G Menghani, E Vee arXiv preprint arXiv:2210.01213, 2022 | | 2022 |
| Approximation Algorithms for Facility Location and Clustering Problems K Trinh University of Maryland, College Park, 2017 | | 2017 |
| A Randomized Local Search Algorithm for the Machine-Part Cell Formation Problem K Trinh, JA Ferland, T Dinh CIRRELT, 2011 | | 2011 |
| AN IMPROVED APPROXIMATION FOR κ-MEDIAN, AND POSITIVE CORRELATION IN BUDGETED OPTIMIZATION J BYRKA, B RYBICKI, T PENSYL, K TRINH, A SRINIVASAN | | |
| A Survey of Algorithms for Capacitated k-median Problems K Trinh | | |
Aravind SrinivasanProfessor of Computer Science and Distinguished University Professor, University of MarylandPreverjeni e-poštni naslov na umd.edu
