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11/28/2022
Machine Learning for Health symposium 2022 – Extended Abstract track
A collection of the extended abstracts that were presented at the 2nd Ma...
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10/19/2022
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts
Performance of machine learning models may differ between training and d...
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09/18/2022
Towards Robust Off-Policy Evaluation via Human Inputs
Off-policy Evaluation (OPE) methods are crucial tools for evaluating pol...
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01/20/2022
Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making
Assessing the effects of a policy based on observational data from a dif...
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09/13/2021
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty
We propose SLTD (`Sequential Learning-to-Defer') a framework for learnin...
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08/27/2021
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing
Machine learning models achieve state-of-the-art performance on many sup...
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06/18/2021
On the Connections between Counterfactual Explanations and Adversarial Examples
Counterfactual explanations and adversarial examples have emerged as cri...
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03/29/2021
Learning Under Adversarial and Interventional Shifts
Machine learning models are often trained on data from one distribution ...
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03/20/2021
An Empirical Framework for Domain Generalization in Clinical Settings
Clinical machine learning models experience significantly degraded perfo...
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02/26/2021
Towards Robust and Reliable Algorithmic Recourse
As predictive models are increasingly being deployed in high-stakes deci...
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11/17/2020
Confounding Feature Acquisition for Causal Effect Estimation
Reliable treatment effect estimation from observational data depends on ...
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09/23/2020
Probabilistic Machine Learning for Healthcare
Machine learning can be used to make sense of healthcare data. Probabili...
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09/22/2020
Ethical Machine Learning in Health Care
The use of machine learning (ML) in health care raises numerous ethical ...
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07/17/2020
Sequential Explanations with Mental Model-Based Policies
The act of explaining across two parties is a feedback loop, where one p...
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06/20/2020
Counterfactually Guided Policy Transfer in Clinical Settings
Reliably transferring treatment policies learned in one clinical environ...
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03/05/2020
What went wrong and when? Instance-wise Feature Importance for Time-series Models
Multivariate time series models are poised to be used for decision suppo...
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07/22/2019
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems
Machine learning based decision making systems are increasingly affectin...
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05/13/2019
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
Translating machine learning (ML) models effectively to clinical practic...
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06/22/2018
xGEMs: Generating Examplars to Explain Black-Box Models
This work proposes xGEMs or manifold guided exemplars, a framework to un...
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08/02/2016