New review paper: "Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges" arxiv.org/abs/2103.11251

Introducing a new paradigm for interpretable ML! treeFarms lets you choose from the set of all near-optimal models instead of giving you just one. Install with: pip install treefarms Paper: arxiv.org/abs/2209.08040 Interface TimberTrek: bit.ly/timbertrek

#NeurIPS2022 @UBC_systopia Interpretable ML Lab FasterRisk quickly produces a collection of high-quality, interpretable risk scoring systems, providing a valuable tool for different fields such as healthcare, finance, and criminal justice. Visit us in Hall J #615 Wed from 4-6 pm.

Duke CS PhD students Haiyang Huang & Yingfan Wang won American Statistical Association (ASA)'s Chambers Statistical SW Award for their Python package PaCMAP, based on a project with Duke Prof Cynthia Rudin & Prof Yaron Shaposhnik, U Rochester Simon School. bit.ly/dukecs-2023-as…

How dangerous is AI? Regulate it before it’s too late thehill.com/opinion/techno…

Dr. Cynthia Rudin won CAUSEWeb 2023 A-mu-sing contest grand prize & 1st place song award! Accompanied by musician-scientists Ed Browne, UNC & Dargan Frierson, Univ. of Washington, Rudin's 3 ML songs have fun bluegrass, compelling lyrics + double entendres. causeweb.org/cause/a-mu-sin…

Which dimension reduction method should you use for data visualization? Check out our blog post on this topic! sites.duke.edu/dimensionreduc…