The MLSys research community is rapidly growing, both in academia and industry. This area historically has not been particularly well addressed by existing Machine Learning or Systems focused conferences. To bridge this gap, we have the MLSys conference for research spanning ML and systems. The goal is to make a home for exceptional research by creating a venue to showcase the work that occurs at the intersection of systems and machine learning and a community with expertise in both areas to evaluate the work.
The MLSys 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.
Important Dates:
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Paper submission deadline: Oct 08, 2021
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Author rebuttal period: Dec 08 to Dec 15, 2021
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Decision notification: Jan 14, 2022
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Camera ready: Mar 04, 2022
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Conference: Apr 11 to Apr 14, 2022
Topics:
Papers are solicited on a broad range of topics, including (but not limited to):
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Efficient model training, inference, and serving
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Distributed and parallel learning algorithms
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Privacy and security for ML applications
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Testing, debugging, and monitoring of ML applications
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Fairness, interpretability and explainability for ML applications
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Data preparation, feature selection, and feature extraction
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ML programming models and abstractions
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ML compilers and runtime
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Programming languages for machine learning
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Visualization of data, models, and predictions
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Specialized hardware for machine learning
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Hardware-efficient ML methods
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Machine Learning for Systems
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Systems for Machine Learning
Organizers:
General Chair: Diana Marculescu
Program Chairs: Yuejie Chi and Carole-Jean Wu