David Durfee

According to our database, David Durfee authored at least 25 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

Instance-Specific Asymmetric Sensitivity in Differential Privacy.

David Durfee

CoRR, 2023

mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization.

Kayhan Behdin, Qingquan Song, Aman Gupta, Ayan Acharya, David Durfee, Borja Ocejo, S. Sathiya Keerthi, Rahul Mazumder

CoRR, 2023

Unbounded Differentially Private Quantile and Maximum Estimation.

David Durfee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving Wireless Power Transfer Efficiency for Distributed Brain Implants using Auto-Tune OVP.

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

Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2023

2022

Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization.

Kayhan Behdin, Qingquan Song, Aman Gupta, David Durfee, Ayan Acharya, S. Sathiya Keerthi, Rahul Mazumder

CoRR, 2022

Heterogeneous Calibration: A post-hoc model-agnostic framework for improved generalization.

David Durfee, Aman Gupta, Kinjal Basu

CoRR, 2022

2021

LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale.

Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad

J. Priv. Confidentiality, 2021

2020

Algorithmic Manipulation of Probability Distributions for Networks and Mechanisms.

David Durfee

PhD thesis, 2020

Determinant-Preserving Sparsification of SDDM Matrices.

David Durfee, John Peebles, Richard Peng, Anup B. Rao

SIAM J. Comput., 2020

Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds.

Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Individual Sensitivity Preprocessing for Data Privacy.

Rachel Cummings, David Durfee

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Optimal Differential Privacy Composition for Exponential Mechanisms.

Jinshuo Dong, David Durfee, Ryan Rogers

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity.

Jinshuo Dong, David Durfee, Ryan Rogers

CoRR, 2019

Efficient Second-Order Shape-Constrained Function Fitting.

David Durfee, Yu Gao, Anup B. Rao, Sebastian Wild

Proceedings of the Algorithms and Data Structures - 16th International Symposium, 2019

Fully dynamic spectral vertex sparsifiers and applications.

David Durfee, Yu Gao, Gramoz Goranci, Richard Peng

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Practical Differentially Private Top-k Selection with Pay-what-you-get Composition.

David Durfee, Ryan M. Rogers

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Fully Dynamic Effective Resistances.

David Durfee, Yu Gao, Gramoz Goranci, Richard Peng

CoRR, 2018

Nearly Tight Bounds for Sandpile Transience on the Grid.

David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao

Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

$\ell_1$ Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent.

David Durfee, Kevin A. Lai, Saurabh Sawlani

Proceedings of the Conference On Learning Theory, 2018

2017

$\ell_1$ Regression using Lewis Weights Preconditioning.

David Durfee, Kevin A. Lai, Saurabh Sawlani

CoRR, 2017

Tight Bounds for Sandpile Transience on the Two-Dimensional Grid up to Polylogarithmic Factors.

David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao

CoRR, 2017

Sampling random spanning trees faster than matrix multiplication.

David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva

Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees.

David Durfee, John Peebles, Richard Peng, Anup B. Rao

Proceedings of the 58th IEEE Annual Symposium on Foundations of Computer Science, 2017

2016

On Fully Dynamic Graph Sparsifiers.

Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng

Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

2015

On the Complexity of Nash Equilibria in Anonymous Games.

Xi Chen, David Durfee, Anthi Orfanou

Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015