Overview
The NeurIPS 2019 Workshop on Safety and Robustness in Decision-Making invites researchers to submit their papers. This workshop aims to address the critical challenges associated with designing decision-making systems that ensure safe interactions and robust performance in various environments. It serves as a platform for both academic and industry experts to discuss advancements and future directions in this vital area of research.
Background & Relevance
As decision-making systems become increasingly integrated into daily life, ensuring their safety and robustness is paramount. These systems are pivotal in high-stakes applications such as autonomous driving, healthcare, and finance. The workshop will explore theoretical and practical advancements that can enhance the reliability of these systems, addressing the growing need for algorithms capable of functioning effectively under uncertainty and environmental changes.
Key Details
- Workshop Dates: December 13 or 14, 2019
- Location: Vancouver
- Paper Submission Deadline: September 22, 2019
- Notification of Acceptance: September 30, 2019
- Submission Format: 4 to 8 pages, NeurIPS 2019 format (not anonymized)
- Submission Email: Safe.Robust.NeurIPS19.Workshop@gmail.com
Eligibility & Participation
This workshop targets researchers and practitioners in the fields of machine learning, robotics, and decision-making systems. Participants are encouraged to share their insights and findings related to safety and robustness in decision-making algorithms.
Submission or Application Guidelines
To participate, interested individuals should prepare their papers according to the specified format and submit them via email as a PDF. Accepted submissions will be presented as posters or through contributed oral presentations, providing an opportunity for authors to engage with attendees and discuss their work.
Additional Context / Real-World Relevance
The workshop addresses pressing issues in the development of decision-making systems, particularly in how they can be designed to operate safely and effectively in unpredictable environments. By fostering discussions around counterfactual reasoning, policy learning under uncertainty, and the balance between robustness and performance, the workshop aims to advance the field significantly.
Conclusion
Researchers and practitioners are encouraged to submit their work to this workshop, contributing to the ongoing discourse on safety and robustness in decision-making systems. This is an excellent opportunity to share knowledge, collaborate, and explore new research avenues in this critical area of AI and machine learning.
Category: CFP & Deadlines
Tags: neurips, decision-making, safety, robustness, machine-learning, autonomous-systems, robotics, healthcare, finance
