10th Conference on Machine Learning and Systems (MLSys 2027)

Key Topics

• Privacy and security for ML applications
• Efficient model training, inference, and serving
• ML programming models and abstractions
• Fairness, interpretability and explainability for ML applications
• Specialized hardware for machine learning
• Programming languages for machine learning
• Distributed and parallel learning algorithms
• Machine Learning for Systems
• Data preparation, feature selection, and feature extraction
• Testing, debugging, and monitoring of ML applications
• Visualization of data, models, and predictions
• ML compilers and runtime
• Systems for Machine Learning
• Hardware-efficient ML methods