1 citations · 1 across the 3 of their papers we have counts for
3 papers
Differential Privacy Under Class Imbalance: Methods and Empirical Insights
Lucas Rosenblatt, Yuliia Lut, Eitan Turok +2
Imbalanced learning occurs in classification settings where the distribution of class-labels is highly skewed in the training data, such as when predicting rare diseases or in frau…
Epsilon*: Privacy Metric for Machine Learning Models
Diana M. Negoescu, Humberto Gonzalez, Saad Eddin Al Orjany +9
We introduce Epsilon*, a new privacy metric for measuring the privacy risk of a single model instance prior to, during, or after deployment of privacy mitigation strategies. The me…
How we browse: Measurement and analysis of digital behavior
Yuliia Lut, Michael Wang, Elissa M. Redmiles +1
Accurately analyzing and modeling online browsing behavior play a key role in understanding users and technology interactions. In this work, we design and conduct a user study to c…