Preferential Mixture-of-Experts: Interpretable Models that Rely on Human
Expertise as much as Possible

Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible

13 January 2021

Melanie F. Pradier

Finale Doshi-Velez

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Papers citing "Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible"

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Title
MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model Alexander Koebler Ingo Thon Florian Buettner 78 0 0 26 Mar 2025
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems Clara Punzi Roberto Pellungrini Mattia Setzu F. Giannotti D. Pedreschi 76 6 0 09 Feb 2024
Sample Efficient Learning of Predictors that Complement Humans Mohammad-Amin Charusaie Hussein Mozannar David Sontag Samira Samadi 73 34 0 19 Jul 2022
Learning-to-defer for sequential medical decision-making under uncertainty Shalmali Joshi S. Parbhoo Finale Doshi-Velez OffRL 100 7 0 13 Sep 2021
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens Maia L. Jacobs Jeffrey He Melanie F. Pradier Barbara D. Lam Andrew C Ahn T. McCoy R. Perlis Finale Doshi-Velez Krzysztof Z. Gajos 120 149 0 01 Feb 2021