Designing monitoring strategies for deployed machine learning
algorithms: navigating performativity through a causal lens

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Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens

20 November 2023

Adarsh Subbaswamy

Alexej Gossmann

Harvineet Singh

Romain Pirracchio

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Papers citing "Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens"

16 / 16 papers shown

Title
Is this model reliable for everyone? Testing for strong calibration Jean Feng Alexej Gossmann Romain Pirracchio N. Petrick Gene Pennello B. Sahiner 52 5 0 28 Jul 2023
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record Conor K. Corbin R. Maclay Aakash Acharya Sreedevi Mony Soumya Punnathanam Rahul Thapa N. Kotecha N. Shah Jonathan Chen 41 18 0 11 Mar 2023
Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions Jean Feng Alexej Gossmann Gene Pennello N. Petrick B. Sahiner Romain Pirracchio 56 3 0 17 Nov 2022
Anticipating Performativity by Predicting from Predictions Celestine Mendler-Dünner Frances Ding Yixin Wang 77 30 0 15 Aug 2022
Challenges in Deploying Machine Learning: a Survey of Case Studies Andrei Paleyes Raoul-Gabriel Urma Neil D. Lawrence 64 403 0 18 Nov 2020
Model updating after interventions paradoxically introduces bias J. Liley S. Emerson Bilal A. Mateen Catalina A Vallejos L. Aslett Sebastian J. Vollmer 65 22 0 22 Oct 2020
Monitoring and explainability of models in production Janis Klaise A. V. Looveren Clive Cox G. Vacanti Alexandru Coca 93 49 0 13 Jul 2020
Performative Prediction Juan C. Perdomo Tijana Zrnic Celestine Mendler-Dünner Moritz Hardt 142 321 0 16 Feb 2020
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 82 752 0 19 Jun 2019
Safe Testing Peter Grünwald R. D. Heide Wouter M. Koolen 64 212 0 18 Jun 2019
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk S. Barbieri James Kemp O. Perez-Concha S. Kotwal M. Gallagher A. Ritchie Louisa R Jorm 56 76 0 21 May 2019
Fairness Without Demographics in Repeated Loss Minimization Tatsunori B. Hashimoto Megha Srivastava Hongseok Namkoong Percy Liang FaML 113 584 0 20 Jun 2018
A likelihood ratio approach to sequential change point detection for a general class of parameters Holger Dette Josua Gösmann 74 35 0 21 Feb 2018
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility A. Chaney Brandon M Stewart Barbara E. Engelhardt CML 211 316 0 30 Oct 2017
Learning (Predictive) Risk Scores in the Presence of Censoring due to Interventions K. Dyagilev Suchi Saria 48 39 0 27 Jul 2015
Counterfactual Reasoning and Learning Systems Léon Bottou J. Peters J. Q. Candela Denis Xavier Charles D. M. Chickering Elon Portugaly Dipankar Ray Patrice Y. Simard Edward Snelson CML OffRL 392 786 0 11 Sep 2012