Call for Papers Industry Track
Paper submissions due: July 12, 2023, 11:59 pm AOE.
- Paper submissions due: July 12, 2023, 11:59 pm AOE.
- Author notifications: August 30, 2023
- Camera ready deadline: September 20, 2023
- Conference Dates: October 25-28, 2023
- Atul Batra, Startup/Product advisor, India
- Milind Gandhe, IIIT Bangalore, India
- Rahul Ghosh, Sr. Director Data Science, Walmart, India
- Veena Mendiratta, Northwestern University, USA
Topics of Interest
This interest include AI/ML systems machine learning applications in all mature and emerging domains, as well as contributions to enabling algorithmic, infrastructure, and optimization methodologies to improve learning efficiency, scaling, and adoption/deployment. The topics include, but are not limited to:
- Efficient model training, inference, and serving
- Distributed and parallel learning algorithms
- Privacy and security for ML applications
- Testing, debugging, and monitoring of ML applications
- Fairness, interpretability and explainability for ML applications
- Data preparation, feature selection, and feature extraction
- ML programming models and abstractions
- Programming languages for machine learning
- Visualization of data, models, and predictions
- Specialized hardware for machine learning
- Hardware-efficient ML methods
- Machine Learning for Systems
- Systems for Machine Learning
- Lessons learned from end-to-end production ML pipelines
- Emerging practices such as AI-ML Ops
- Systems for Generative AI
- Generative AI use-cases
- Benchmarking and performance studies for Generative AI tools
All submissions will be single blind. Authors are allowed to post their paper on arXiv or other public forums. Key dates related to the reviewing process will be shared soon.
Research papers must not exceed 6 pages, including any appendix, with an unlimited number of pages containing only bibliography. Only electronic submissions in PDF format using the ACM sigconf template (see https://www.acm.org/publications/proceedings-template) will be considered. The submissions will be through https://cmt3.research.microsoft.com/AIMLSystems2023.