L4DC2020: Learning for Dynamics and Control 2020 University of California Berkeley, CA, United States, June 10-11, 2020 |
Conference website | http://l4dc.org |
Submission link | https://easychair.org/conferences/?conf=l4dc2020 |
Submission deadline | December 20, 2019 |
Over the next decade, the biggest generator of data is expected to be devices which sense and control the physical world.
This explosion of real-time data that is emerging from the physical world requires a rapprochement of areas such as machine learning, control theory, and optimization. While control theory has been firmly rooted in tradition of model-based design, the availability and scale of data (both temporal and spatial) will require rethinking of the foundations of our discipline. From a machine learning perspective, one of the main challenges going forward is to go beyond pattern recognition and address problems in data driven control and optimization of dynamical processes.
Our overall goal is to create a new community of people that think rigorously across the disciplines, asks new questions, and develops the foundations of this new scientific area.
Topics
We invite submissions of short papers addressing topics including:
- Foundations of learning of dynamics models
- System identification
- Optimization for machine learning
- Data-driven optimization for dynamical systems
- Distributed learning over distributed systems
- Reinforcement learning for physical systems
- Safe reinforcement learning and safe adaptive control
- Statistical learning for dynamical and control systems
- Bridging model-based and learning-based dynamical and control systems
- Physics-constrained learning
- Physical learning in dynamical and control systems applications in robotics, autonomy, transportation systems, cognitive systems, cognitive systems, neuroscience, etc.
While the conference is open to any topic on the interface between machine learning, control, optimization and related areas, its primary goal is to address scientific and application challenges in real-time physical processes modeled by dynamical or control systems.
Submission Guidelines
All accepted papers will be presented as posters at this conference. A selected set of 10 papers deemed particularly exceptional by the program committee will be presented as 15 minute oral talks. At least one of each paper’s authors should be present at the conference to present the work. Accepted papers will be published electronically in the Proceedings of Machine Learning Research (PMLR). The authors of accepted papers will have the option of opting-out of the proceedings in favor of a 1-page extended abstract. The full paper reviewed will then be placed on the arXiv repository but not indexed by the conference.
Submissions that are substantially similar to papers that have been previously published, accepted for publication, or submitted in parallel to other peer-reviewed conferences with proceedings or journals may not be submitted to L4DC.
Important Dates
- Paper submission deadline: December 6, 2019, 5:00 PM EST
- Author notification: March 1, 2020.
- Conference: June 10-11, 2020.
Submission instructions
- Submissions are limited to 6 pages in PMLR format (LaTeX Style Sheet).
- L4DC reviewing is single blind.
- We will begin accepting submissions via EasyChair on November 1, 2020.
- The deadline for submissions is 5:00 PM EST on December 6, 2019.
- Please contact the program chairs at L4DC2020@gmail.com if you have any questions about the policy or technical issues with the submission process.
Contact
Please contact the program chairs at L4DC2020@gmail.com if you have any questions about the policy or technical issues with the submission process.