10 citations · 24 across the 8 of their papers we have counts for
18 papers
Denoising neural networks for magnetic resonance spectroscopy
Natalie Klein, Amber J. Day, Harris Mason +2
In many scientific applications, measured time series are corrupted by noise or distortions. Traditional denoising techniques often fail to recover the signal of interest, particul…
Balance is key: Private median splits yield high-utility random trees
Shorya Consul, Sinead A. Williamson
Random forests are a popular method for classification and regression due to their versatility. However, this flexibility can come at the cost of user privacy, since training rando…
Federating Recommendations Using Differentially Private Prototypes
Mónica Ribero, Jette Henderson, Sinead Williamson +1
Machine learning methods allow us to make recommendations to users in applications across fields including entertainment, dating, and commerce, by exploiting similarities in users'…
Distributed, partially collapsed MCMC for Bayesian Nonparametrics
Avinava Dubey, Michael Minyi Zhang, Eric P. Xing +1
Bayesian nonparametric (BNP) models provide elegant methods for discovering underlying latent features within a data set, but inference in such models can be slow. We exploit the f…
A Nonparametric Bayesian Model for Sparse Dynamic Multigraphs
Elahe Ghalebi, Hamidreza Mahyar, Radu Grosu +2
As the availability and importance of temporal interaction data--such as email communication--increases, it becomes increasingly important to understand the underlying structure th…
Avoiding Resentment Via Monotonic Fairness
Guy W. Cole, Sinead A. Williamson
Classifiers that achieve demographic balance by explicitly using protected attributes such as race or gender are often politically or culturally controversial due to their lack of…