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Learning to Induce Causal Structure


Apr 11, 2022
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jorg Bornschein, Theophane Weber, Anirudh Goyal, Matthew Botvinic, Michael Mozer, Danilo Jimenez Rezende


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Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness


Feb 23, 2022
Carolyn Ashurst, Ryan Carey, Silvia Chiappa, Tom Everitt

* In Proceedings of the AAAI 2022 Conference 

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Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?


Feb 02, 2022
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alex Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine Heller, Silvia Chiappa, Alexander D'Amour


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Statistical discrimination in learning agents


Oct 21, 2021
Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo

* 29 pages, 10 figures 

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Prequential MDL for Causal Structure Learning with Neural Networks


Jul 02, 2021
Jorg Bornschein, Silvia Chiappa, Alan Malek, Rosemary Nan Ke


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Fairness with Continuous Optimal Transport


Jan 06, 2021
Silvia Chiappa, Aldo Pacchiano


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Fairness in Machine Learning


Dec 31, 2020
Luca Oneto, Silvia Chiappa

* Recent Trends in Learning From Data. Studies in Computational Intelligence, vol 896. Springer, Cham, 2020 

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Explicit-Duration Markov Switching Models


Sep 12, 2019
Silvia Chiappa

* Foundations and Trends in Machine Learning, Volume 7, Issue 6, pages 803-886, 2014 

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Wasserstein Fair Classification


Jul 28, 2019
Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa

* Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019 

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Unsupervised Separation of Dynamics from Pixels


Jul 20, 2019
Silvia Chiappa, Ulrich Paquet

* METRON, Springer, 2019 

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