We propose JAWS, a series of wrapper methods for distribution-free
uncer...
Human space exploration beyond low Earth orbit will involve missions of
...
Space biology research aims to understand fundamental effects of spacefl...
When data contains measurement errors, it is necessary to make assumptio...
The use of observational time series data to assess the impact of multi-...
As the use of machine learning in safety-critical domains becomes widesp...
Shifts in environment between development and deployment cause classical...
Recent work addressing model reliability and generalization has resulted...
Recent work addressing model reliability and generalization has resulted...
This document serves as a brief overview of the "Safe and Reliable Machi...
Machine learning can help personalized decision support by learning mode...
Measurement error in observational datasets can lead to systematic bias ...
The Computing Community Consortium (CCC), along with the White House Off...
To use machine learning in high stakes applications (e.g. medicine), we ...
To use machine learning in high stakes applications (e.g. medicine), we ...
Classical supervised learning produces unreliable models when training a...
Time series data that are not measured at regular intervals are commonly...
Predictive models can fail to generalize from training to deployment
env...
Missing data and noisy observations pose significant challenges for reli...
Treatment effects can be estimated from observational data as the differ...
Making a good decision involves considering the likely outcomes under ea...
We study the problem of estimating the continuous response over time to
...
Predictive models are finding an increasing number of applications in ma...
For many complex diseases, there is a wide variety of ways in which an
i...
This paper addresses fully automated multi-person tracking in complex
en...
A large and diverse set of measurements are regularly collected during a...
This paper proposes a nonparametric Bayesian method for exploratory data...