Call for Workshops/Tutorials:

Machine Learning for Systems at NeurIPS 2023

Abstract or Paper Registration Deadline
September 29, 2023
Final Submission Deadline
September 29, 2023

Machine Learning for Systems at NeurIPS 2023

Important Dates

  • Competition Start Date: Late August, 2023 (to be announced)
  • Paper Submission Deadline: September 29, 2023 by midnight (Anywhere in the World)
  • Paper Acceptance Notifications: October 27, 2023
  • Competition Submission Deadline: November 17, 2023
  • Workshop: December 16, 2023 (tentatively scheduled)

NeurIPS 2023 Machine Learning for Systems Call for Papers

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.

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:

1.   Using LLMs for systems challenges, such as program synthesis for hardware and other specialized domains.

2.   Applying ML to systems issues that emerge from large-scale training and serving, such as compiler partitioning schemes for training LLMs across thousands of GPU or TPU devices.

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.

You can find accepted papers to the previous iteration of ML for Systems from NeurIPS 2018, 2019, 2020, 20212022, and ISCA 2019.

Areas of interest:

  • Supervised, unsupervised, and reinforcement learning research with applications to:
    • Systems software
    • Runtime systems
    • Distributed systems
    • Security
    • Compilers, data structures, and code optimization
    • Databases
    • Computer architecture, microarchitecture, and accelerators
    • Circuit design and layout
    • Interconnects and Networking
    • Storage
    • Datacenters
    • Programming Languages
  • Representation learning for hardware and software
  • Optimization of computer systems and software
  • Systems modeling and simulation
  • Implementations of ML for systems and challenges
  • High quality datasets for ML for systems problems
  • Emerging applications
    • Using LLMs for systems
    • Using ML for challenges in large-scale machine learning systems for ML training and serving

Submission Instructions

We welcome submissions of up to 4 pages (not including references). This is not a strict limit, but authors are encouraged to adhere to it if possible. All submissions must be in PDF format and should follow the NeurIPS 2023 format. Submissions do not have to be anonymized.

Please submit your paper no later than September 29th, 2023 midnight anywhere in the world to the OpenReview submission site.

Competition Track

This year, our workshop introduces a competition track to showcase and explore state-of-the-art techniques in ML for systems. We hope that the first iteration of the competition track will serve as an initiative to encourage industry to share ML for systems data and research based on real-world production data. The top winners have the opportunities to share their technical reports to receive sponsor prizes.

The instructions for the competition track will be posted soon. If you would like to be notified when the competition is up, please join:

Organizing Committee

  • Beidi Chen, CMU
  • Dan Zhang, Google DeepMind
  • Divya Mahajan, Microsoft and Georgia Tech
  • Mangpo Phothilimthana, Google DeepMind
  • Mimee Xu, NYU
  • Yawen Wang, Google

Competition Committee

  • Bryan Perozzi, Google Research
  • Mangpo Phothilimthana, Google DeepMind
  • Sami Abu-el-haija, Google Research

Contact Us

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