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View MLSys 2022 sponsors »Become a 2022 Sponsor »Conference Overview
The Conference on Machine Learning and Systems targets research at the intersection of machine learning and systems. The conference aims to elicit new connections amongst these fields, including identifying best practices and design principles for learning systems, as well as developing novel learning methods and theory tailored to practical machine learning workflows. Topics include:
- Efficient model training, inference, and serving
- Privacy and security for ML applications
- Fairness, interpretability and explainability for ML applications
- ML programming models and abstractions
- Programming languages for machine learning
- Specialized hardware for machine learning
- Machine Learning for Systems
- Distributed and parallel learning algorithms
- Testing, debugging, and monitoring of ML applications
- Data preparation, feature selection, and feature extraction
- ML compilers and runtime
- Visualization of data, models, and predictions
- Hardware-efficient ML methods
- Systems for Machine Learning
Important Dates
| Conference Sessions | Mon Aug 29th through Sep 1st |
| SponsorPortalOpen | Nov 10 '21 07:07 PM UTC * | |
| CameraReadyDeadline | Mar 18 '22 08:00 PM UTC * | |
| Registration Opens | Jun 20 '22 08:00 PM UTC * | |
| StudentTravelGrantApplicationDeadline | Jun 29 '22(Anywhere on Earth) | |
| StudentTravelGrantNotifications | Jul 07 '22 01:00 AM UTC * | |
| Early pricing before this date. | Aug 01 '22 08:00 PM UTC * | |
| Sponsor Payment Deadline | Aug 06 '22 01:00 AM UTC * | |
| Last chance for a refund on registration fees | Aug 12 '22 06:59 AM UTC * | |
| SlidesLive recordings due | Aug 14 '22(Anywhere on Earth) | |
| All dates » | Timezone: » |
Organizing Committee
|
General Chair Diana Marculescu, UT Austin Program Chairs Yuejie Chi, CMU Workshop and Tutorial Chairs Chris De Sa, Cornell Workflow Chair Boyue Li, CMU |
Sponsor Chair Wen-ming Ye, Amazon Publications Chair Jakub Konečný, Google Artifact Evaluation Chairs Tianqi Chen, CMU Panel and Young Professional Activities Chair Udit Gupta, Harvard/FAIR |
The organizers can be contacted here.
Board
Ameet Talwalkar (President)
Virginia Smith (Secretary)
Inderjit Dhillon (Treasurer)
Matei Zaharia
Dimitris Papailiopoulos
Vivienne Sze
Alex Dimakis
Alex Smola
Ion Stoica
Steering Committee
Jennifer Chayes
Bill Dally
Jeff Dean
Michael I. Jordan
Yann LeCun
Fei-Fei Li
Alex Smola
Dawn Song
Eric Xing
Mission Statement
The non-profit corporation that runs MLSys aims to foster the exchange of research advances at the intersection of machine learning and systems, principally by hosting an annual interdisciplinary academic conference with the highest ethical standards for a diverse and inclusive community.
About the Conference
The MLSys community recognized that many critical future challenges are at the intersection of Machine Learning and Systems. The community was created to solve these exciting problems by recognizing the needs for scaling interdisciplinary collaboration as well as the importance of working together between industry and academia.
The community has come together to create a new conference for research spanning ML and systems, MLSys. The goal is to make a home for exceptional new research, a venue to showcase the growing trend, and more importantly a way to scale ever more complex research collaboration.
The steering committee and program committees consist of 50 leading members of emerging machine learning systems area coming from industry and academia with expertise ranging from machine learning to systems to security. The MLSys community welcomes industry participation and sponsorships, we believe the investment will pay dividend in both technology advancement and industry growth for years to come.