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Interpretable ML Lab @InterpretMLLab

Joined September 2022
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Interpretable ML Lab @InterpretMLLab

3 years ago

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

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Duke CompSci @dukecompsci

3 years ago

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…

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Margo Seltzer @margo_seltzer

3 years ago

#NeurIPS2022 @UBC_Systopia @InterpretMLLab 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.

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Interpretable ML Lab @InterpretMLLab

3 years ago

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

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