Machine Learning for Systems is an interdisciplinary workshop that brings together researchers in computer systems and machine learning. This workshop is meant to serve as a platform to promote discussions between researchers in these target areas.
Call for Papers
We invite submission of up to 4-page extended abstracts in the broad area of using machine learning in the design of computer systems. We are especially interested in submissions that move beyond using machine learning to replace numerical heuristics.
This year, we additionally look for
- Using LLMs for systems, such as program synthesis for hardware and other specialized domains, and
- Using ML for systems issues that emerge from large scale training and serving, such as compiler partitioning schemes for training LLMs across GPUs and TPUs located globally.
Accepted papers will be made available on the workshop website, but there will be no formal proceedings. Authors may therefore publish their work in other journals or conferences. The workshop will include invited talks from industry and academia as well as oral and poster presentations by workshop participants.
For accepted papers, please update the camera-ready manuscript on OpenReview by November 17th AoE.
Please see instructions below:
- The camera-ready template is the same as the one used for submission, which is same as NeurIPS papers. Kindly use the Final package. We have made some minor changes to the format. Please use the template (.zip) attached.
- There is a hard page limit of 4 pages (excluding references and Appendix).
- Appendix and references do not have a limit