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ORCIDDavid Durfee
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2020 – today
- 2023
[c14]Vincent W. Leung
, Ah-Hyoung Lee, Jihun Lee, Sravya Alluri, Julian Alonzo, Luke Mello, Brett Beyer, David Durfee, Wing-Fat Andy Lau, Peter M. Asbeck, Lawrence E. Larson, Farah Laiwalla, Arto V. Nurmikko:
Improving Wireless Power Transfer Efficiency for Distributed Brain Implants using Auto-Tune OVP. BioCAS 2023: 1-5- [c13]David Durfee:
Unbounded Differentially Private Quantile and Maximum Estimation. NeurIPS 2023 - [i19]Kayhan Behdin, Qingquan Song, Aman Gupta, Ayan Acharya, David Durfee, Borja Ocejo, S. Sathiya Keerthi, Rahul Mazumder:
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization. CoRR abs/2302.09693 (2023) - [i18]David Durfee:
Unbounded Differentially Private Quantile and Maximum Estimation. CoRR abs/2305.01177 (2023) - [i17]David Durfee:
Instance-Specific Asymmetric Sensitivity in Differential Privacy. CoRR abs/2311.14681 (2023) - 2022
- [i16]David Durfee, Aman Gupta, Kinjal Basu:
Heterogeneous Calibration: A post-hoc model-agnostic framework for improved generalization. CoRR abs/2202.04837 (2022) - [i15]Kayhan Behdin, Qingquan Song, Aman Gupta, David Durfee, Ayan Acharya, S. Sathiya Keerthi, Rahul Mazumder:
Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization. CoRR abs/2212.04343 (2022) - 2021
- [j2]Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad:
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale. J. Priv. Confidentiality 11(3) (2021) - 2020
- [b1]David Durfee:
Algorithmic Manipulation of Probability Distributions for Networks and Mechanisms. Georgia Institute of Technology, Atlanta, GA, USA, 2020 - [j1]David Durfee, John Peebles, Richard Peng, Anup B. Rao:
Determinant-Preserving Sparsification of SDDM Matrices. SIAM J. Comput. 49(4) (2020) - [c12]Jinshuo Dong, David Durfee, Ryan Rogers:
Optimal Differential Privacy Composition for Exponential Mechanisms. ICML 2020: 2597-2606 - [c11]Rachel Cummings, David Durfee:
Individual Sensitivity Preprocessing for Data Privacy. SODA 2020: 528-547 - [c10]Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun:
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds. SODA 2020: 1300-1319 - [i14]Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad:
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale. CoRR abs/2002.05839 (2020)
2010 – 2019
- 2019
- [c9]David Durfee, Ryan M. Rogers:
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. NeurIPS 2019: 3527-3537 - [c8]David Durfee, Yu Gao, Gramoz Goranci, Richard Peng:
Fully dynamic spectral vertex sparsifiers and applications. STOC 2019: 914-925 - [c7]David Durfee, Yu Gao, Anup B. Rao, Sebastian Wild:
Efficient Second-Order Shape-Constrained Function Fitting. WADS 2019: 395-408 - [i13]David Durfee, Yu Gao, Anup B. Rao, Sebastian Wild:
Efficient Second-Order Shape-Constrained Function Fitting. CoRR abs/1905.02149 (2019) - [i12]David Durfee, Ryan Rogers:
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. CoRR abs/1905.04273 (2019) - [i11]David Durfee, Yu Gao, Gramoz Goranci, Richard Peng:
Fully Dynamic Spectral Vertex Sparsifiers and Applications. CoRR abs/1906.10530 (2019) - [i10]David Durfee, Laxman Dhulipala, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun:
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds. CoRR abs/1908.01956 (2019) - [i9]Jinshuo Dong, David Durfee, Ryan Rogers:
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity. CoRR abs/1909.13830 (2019) - 2018
- [c6]David Durfee, Kevin A. Lai, Saurabh Sawlani:
$\ell_1$ Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent. COLT 2018: 1626-1656 - [c5]David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao:
Nearly Tight Bounds for Sandpile Transience on the Grid. SODA 2018: 605-624 - [i8]David Durfee, Yu Gao, Gramoz Goranci, Richard Peng:
Fully Dynamic Effective Resistances. CoRR abs/1804.04038 (2018) - [i7]Rachel Cummings, David Durfee:
Individual Sensitivity Preprocessing for Data Privacy. CoRR abs/1804.08645 (2018) - 2017
- [c4]David Durfee, John Peebles, Richard Peng, Anup B. Rao:
Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. FOCS 2017: 926-937 - [c3]David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva:
Sampling random spanning trees faster than matrix multiplication. STOC 2017: 730-742 - [i6]David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao:
Tight Bounds for Sandpile Transience on the Two-Dimensional Grid up to Polylogarithmic Factors. CoRR abs/1704.04830 (2017) - [i5]David Durfee, John Peebles, Richard Peng, Anup B. Rao:
Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. CoRR abs/1705.00985 (2017) - [i4]David Durfee, Kevin A. Lai, Saurabh Sawlani:
$\ell_1$ Regression using Lewis Weights Preconditioning. CoRR abs/1708.07821 (2017) - 2016
- [c2]Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng:
On Fully Dynamic Graph Sparsifiers. FOCS 2016: 335-344 - [i3]Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng:
On Fully Dynamic Graph Sparsifiers. CoRR abs/1604.02094 (2016) - [i2]David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva:
Sampling Random Spanning Trees Faster than Matrix Multiplication. CoRR abs/1611.07451 (2016) - 2015
- [c1]Xi Chen, David Durfee, Anthi Orfanou:
On the Complexity of Nash Equilibria in Anonymous Games. STOC 2015: 381-390 - 2014
- [i1]Xi Chen, David Durfee, Anthi Orfanou:
On the Complexity of Nash Equilibria in Anonymous Games. CoRR abs/1412.5681 (2014)
Coauthor Index
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