*Call for Papers: Special Issue of Machine Learning on Safe and Fair
Machine Learning*
We invite submissions to a special issue of the Machine Learning Journal.
*Submission deadline:* November 15, 2021
*Website*: https://www.springer.com/journal/10994/updates/18786592
<https://www.springer.com/journal/10994/updates/18786592>
We encourage early submissions, which will be reviewed continuously
before the deadline.
*
*
*Topics of Interest*
We seek contributions in, but are not limited to, the following topics:
* Fairness and/or safety in machine learning
* Safe reinforcement learning
* Robust and risk-sensitive decision making
* Safe robot control
* Bias in machine learning
* Adversarial examples in machine learning and defense mechanisms
* Applications of transparency and interpretability to safety and
fairness in machine learning
* Safety and interpretability by having a human in the loop
* Verification techniques to ensure safety and robustness
* Backdoors in machine learning
Contributions must contain new, unpublished, original and fundamental
work related to the Machine Learning Journal’s mission.
Best regards,
Guest Editors
Dana Drachsler Cohen (Technion, Israel Institute of Technology)
Javier García (Universidad Carlos III de Madrid)
Mohammad Ghavamzadeh (Google Research)
Marek Petrik (University of New Hampshire)
Philip S. Thomas (University of Massachusetts)
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