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Activity Details

498 Thu, 8/6/2020, 10:00 AM - 2:00 PM Virtual
Modern Machine Learning — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Rebecca North, North Carolina State University
Random Forest Kernels: Utility and Insights for Interpretable Statistical Learning
Dai Feng, AbbVie; Richard Baumgartner, Merck
Uniform Regret Bounds for Quantile Regression Tree Process in Offline and Online Settings
Fei Fang, Duke University; Alexandre Belloni, Duke University
Deep Learning with Gaussian Differential Privacy
Zhiqi Bu, University of Pennsylvania
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation
Rungang Han, University of Wisconsin-Madison; Rebecca Willett, University of Chicago; Anru Zhang, University of Wisconsin-Madison
Nonparametric Individual Treatment Effect Estimation for Survival Data with Random Forests
Denis Larocque, HEC Montreal; Sami Tabib, HEC Montreal
Sequential Changepoint Detection for Classifier Label Shift
Ciaran Evans, Carnegie Mellon University; Max G'Sell, Carnegie Mellon University
Machine Learning Oracle to Guide Statistical Data Processing
Lucas Koepke, National Institute of Standards and Techology; Michael Frey, National Institute of Standards and Technology