4 citations · 4 across the 3 of their papers we have counts for
3 papers
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…
Sales Channel Optimization via Simulations Based on Observational Data with Delayed Rewards: A Case Study at LinkedIn
Diana M. Negoescu, Pasha Khosravi, Shadow Zhao +3
Training models on data obtained from randomized experiments is ideal for making good decisions. However, randomized experiments are often time-consuming, expensive, risky, infeasi…
MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry
Qingzhu Gao, Humberto Gonzalez, Parvez Ahammad
Development of interpretable machine learning models for clinical healthcare applications has the potential of changing the way we understand, treat, and ultimately cure, diseases…