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Invited Paper Session

Promoting Interpretable, Trustworthy, and Ethical Machine Learning with Statistics

Thu, Aug 7, 8:30 AM - 10:20 AM Room CC-Davidson Ballroom B Music City Center

Lili ZhengOrganizerYuchen ZhouChair

Section on Statistical Learning and Data Science co: Section on Nonparametric Statistics Applied

4 Presentations

Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance

8:35 AM - 9:00 AM

Linjun Zhang (Rutgers University)

Large Language Models Algorithmic Fairness

Targeted Learning Inference for Variable Importance and Fairness in Machine Learning

9:00 AM - 9:25 AM

Giles Hooker (University of Pennsylvania)

Interpretable Machine Learning targetted learning feature attribution fairness xAI

A model-agnostic ensemble framework with built-in LOCO feature importance inference

9:25 AM - 9:50 AM

Feature interaction, random ensembles, uncertainty quantification

Powerful and valid interactive subgroup selection via machine learning

9:50 AM - 10:15 AM

Lucas Janson (Harvard University)

Subgroup discovery Causal inference Interactive procedures

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