David Durfee

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 33

Top Topics

Differential Privacy

Top Venues

Publications

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 (2023)
David Durfee
Unbounded Differentially Private Quantile and Maximum Estimation. CoRR (2023)
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)
David Durfee
Unbounded Differentially Private Quantile and Maximum Estimation. NeurIPS (2023)
David Durfee
Instance-Specific Asymmetric Sensitivity in Differential Privacy. CoRR (2023)
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 (2022)
David Durfee, Aman Gupta, Kinjal Basu
Heterogeneous Calibration: A post-hoc model-agnostic framework for improved generalization. CoRR (2022)
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)
David Durfee, John Peebles, Richard Peng, Anup B. Rao
Determinant-Preserving Sparsification of SDDM Matrices. SIAM J. Comput. 49 (4) (2020)
Jinshuo Dong, David Durfee, Ryan Rogers
Optimal Differential Privacy Composition for Exponential Mechanisms. ICML (2020)
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 (2020)
Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds. SODA (2020)
Rachel Cummings, David Durfee
Individual Sensitivity Preprocessing for Data Privacy. SODA (2020)
David Durfee, Ryan M. Rogers
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. NeurIPS (2019)
David Durfee, Yu Gao, Anup B. Rao, Sebastian Wild
Efficient Second-Order Shape-Constrained Function Fitting. CoRR (2019)
Jinshuo Dong, David Durfee, Ryan Rogers
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity. CoRR (2019)
David Durfee, Yu Gao, Anup B. Rao, Sebastian Wild
Efficient Second-Order Shape-Constrained Function Fitting. WADS (2019)
David Durfee, Yu Gao, Gramoz Goranci, Richard Peng
Fully Dynamic Spectral Vertex Sparsifiers and Applications. CoRR (2019)
David Durfee, Laxman Dhulipala, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds. CoRR (2019)
David Durfee, Yu Gao, Gramoz Goranci, Richard Peng
Fully dynamic spectral vertex sparsifiers and applications. STOC (2019)
David Durfee, Ryan Rogers
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. CoRR (2019)
Rachel Cummings, David Durfee
Individual Sensitivity Preprocessing for Data Privacy. CoRR (2018)
David Durfee, Kevin A. Lai, Saurabh Sawlani
$\ell_1$ Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent. COLT (2018)
David Durfee, Yu Gao, Gramoz Goranci, Richard Peng
Fully Dynamic Effective Resistances. CoRR (2018)
David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao
Nearly Tight Bounds for Sandpile Transience on the Grid. SODA (2018)
David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva
Sampling random spanning trees faster than matrix multiplication. STOC (2017)
David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao
Tight Bounds for Sandpile Transience on the Two-Dimensional Grid up to Polylogarithmic Factors. CoRR (2017)
David Durfee, Kevin A. Lai, Saurabh Sawlani
$\ell_1$ Regression using Lewis Weights Preconditioning. CoRR (2017)
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)
David Durfee, John Peebles, Richard Peng, Anup B. Rao
Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. CoRR (2017)
Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng
On Fully Dynamic Graph Sparsifiers. FOCS (2016)
David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva
Sampling Random Spanning Trees Faster than Matrix Multiplication. CoRR (2016)
Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng
On Fully Dynamic Graph Sparsifiers. CoRR (2016)
Xi Chen, David Durfee, Anthi Orfanou
On the Complexity of Nash Equilibria in Anonymous Games. STOC (2015)
Xi Chen, David Durfee, Anthi Orfanou
On the Complexity of Nash Equilibria in Anonymous Games. CoRR (2014)