45 citations · 47 across the 6 of their papers we have counts for
6 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…
Unlocking Sales Growth: Account Prioritization Engine with Explainable AI
Suvendu Jena, Jilei Yang, Fangfang Tan
B2B sales requires effective prediction of customer growth, identification of upsell potential, and mitigation of churn risks. LinkedIn sales representatives traditionally relied o…
Confounder Analysis in Measuring Representation in Product Funnels
Jilei Yang, Wentao Su
This paper discusses an application of Shapley values in the causal inference field, specifically on how to select the top confounder variables for coarsened exact matching method…
Fast TreeSHAP: Accelerating SHAP Value Computation for Trees
Jilei Yang
SHAP (SHapley Additive exPlanation) values are one of the leading tools for interpreting machine learning models, with strong theoretical guarantees (consistency, local accuracy) a…
CrystalCandle: A User-Facing Model Explainer for Narrative Explanations
Jilei Yang, Diana Negoescu, Parvez Ahammad
Predictive machine learning models often lack interpretability, resulting in low trust from model end users despite having high predictive performance. While many model interpretat…
Estimating Time-Varying Graphical Models
Jilei Yang, Jie Peng
In this paper, we study time-varying graphical models based on data measured over a temporal grid. Such models are motivated by the needs to describe and understand evolving intera…