| 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 | 69 | 2017 |
| On fully dynamic graph sparsifiers I Abraham, D Durfee, I Koutis, S Krinninger, R Peng 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS …, 2016 | 69 | 2016 |
| LinkedIn's Audience Engagements API: A privacy preserving data analytics system at scale R Rogers, S Subramaniam, S Peng, D Durfee, S Lee, SK Kancha, ... arXiv preprint arXiv:2002.05839, 2020 | 51 | 2020 |
| Practical differentially private top-k selection with pay-what-you-get composition D Durfee, RM Rogers Advances in Neural Information Processing Systems 32, 2019 | 48 | 2019 |
| Optimal differential privacy composition for exponential mechanisms J Dong, D Durfee, R Rogers International Conference on Machine Learning, 2597-2606, 2020 | 38 | 2020 |
| Fully dynamic spectral vertex sparsifiers and applications D Durfee, Y Gao, G Goranci, R Peng Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 35 | 2019 |
| 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 | 33 | 2017 |
| On the complexity of nash equilibria in anonymous games X Chen, D Durfee, A Orfanou Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015 | 33 | 2015 |
| Individual sensitivity preprocessing for data privacy R Cummings, D Durfee Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 26 | 2020 |
| Parallel batch-dynamic graphs: Algorithms and lower bounds L Dhulipala, D Durfee, J Kulkarni, R Peng, S Sawlani, X Sun Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 24 | 2020 |
| Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent D Durfee, KA Lai, S Sawlani Conference On Learning Theory, 1626-1656, 2018 | 15 | 2018 |
| Fully dynamic effective resistances D Durfee, Y Gao, G Goranci, R Peng arXiv preprint arXiv:1804.04038, 2018 | 8 | 2018 |
| Determinant-preserving sparsification of SDDM matrices D Durfee, J Peebles, R Peng, AB Rao SIAM Journal on Computing 49 (4), FOCS17-350-FOCS17-408, 2020 | 5 | 2020 |
| Nearly tight bounds for sandpile transience on the grid D Durfee, M Fahrbach, Y Gao, T Xiao Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018 | 5 | 2018 |
| Practical differentially private top-k selection with paywhat-you-get composition D Durfee, RM Rogers Advances in Neural Information Processing Systems 32, 8-14, 0 | 5 | |
| Parallel batch-dynamic graphs: Algorithms and lower bounds D Durfee, L Dhulipala, J Kulkarni, R Peng, S Sawlani, X Sun arXiv preprint arXiv:1908.01956, 2019 | 4 | 2019 |
| On fully dynamic graph sparsifiers. CoRR, abs/1604.02094, 2016 I Abraham, D Durfee, I Koutis, S Krinninger, R Peng | 4 | 2016 |
| Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization K Behdin, Q Song, A Gupta, D Durfee, A Acharya, S Keerthi, R Mazumder arXiv preprint arXiv:2212.04343, 2022 | 1 | 2022 |
| Efficient Second-Order Shape-Constrained Function Fitting D Durfee, Y Gao, AB Rao, S Wild Algorithms and Data Structures: 16th International Symposium, WADS 2019 …, 2019 | 1 | 2019 |
| Unbounded Differentially Private Quantile and Maximum Estimation D Durfee arXiv preprint arXiv:2305.01177, 2023 | | 2023 |
