Machine Learning

About this journal

Machine Learning is the premier international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of task types.

Aims and scope

Machine Learning publishes research on computational approaches to learning, covering theoretical foundations, algorithms, and applications across all areas of machine learning.

Topics covered include:

• Supervised and unsupervised learning
• Reinforcement learning
• Deep learning architectures
• Probabilistic graphical models
• Optimization methods for ML
• Transfer learning and domain adaptation
• Online and incremental learning
• Learning theory and generalization

For authors