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12/21/2022
Adapting to Latent Subgroup Shifts via Concepts and Proxies
We address the problem of unsupervised domain adaptation when the source...
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07/21/2022
Detecting and Preventing Shortcut Learning for Fair Medical AI using Shortcut Testing (ShorT)
Machine learning (ML) holds great promise for improving healthcare, but ...
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05/31/2022
A Reduction to Binary Approach for Debiasing Multiclass Datasets
We propose a novel reduction-to-binary (R2B) approach that enforces demo...
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04/08/2022
Disability prediction in multiple sclerosis using performance outcome measures and demographic data
Literature on machine learning for multiple sclerosis has primarily focu...
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02/26/2022
Healthsheet: Development of a Transparency Artifact for Health Datasets
Machine learning (ML) approaches have demonstrated promising results in ...
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02/02/2022
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?
Fairness and robustness are often considered as orthogonal dimensions wh...
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06/16/2021
Best of both worlds: local and global explanations with human-understandable concepts
Interpretability techniques aim to provide the rationale behind a model'...
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12/03/2020
Concept-based model explanations for Electronic Health Records
Recurrent Neural Networks (RNNs) are often used for sequential modeling ...
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11/06/2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
ML models often exhibit unexpectedly poor behavior when they are deploye...
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05/16/2019
Inferring Javascript types using Graph Neural Networks
The recent use of `Big Code' with state-of-the-art deep learning methods...
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04/30/2018