The IEEE MLSP 2026 invites paper submissions that are devoted to the most recent and exciting advances in machine learning for signal processing.
Please review our paper submission guidelines before submitting.
The topics covered in MLSP 2026 include but are not limited to:
- Advanced optimization methods
- Bayesian and probabilistic inference
- Machine learning on graphs
- Distributed/federated learning
- Domain-aware processing
- Information theory for learning
- Learning from multimodal data
- Machine intelligence for education
- Meta/transfer learning
- Privacy and fairness in machine learning
- Tensor-based signal processing
- Applications of machine learning
- Biosignal processing and learning
- Decentralised and edge communication, computing, and processing
- Deep learning techniques
- Graph representation learning
- Kernel and dictionary learning methods
- Learning theory and algorithms
- Matrix and tensor learning methods
- Subspace and manifold learning
- Virtual and augmented reality data processing
- Large Language Models
- Multimodal Machine Learning
- MLSP in Financial Engineering (Fintech)
- MLSP in Healthcare and Aged Care
- MLSP in Disaster Management
- MLSP in Wireless Communications
- MLSP in Neuroscience Applications
Submission of papers: Authors are invited to submit 6 pages full-length papers, including figures and references. All accepted and presented papers will be published in and indexed by IEEE Xplore.
Important Dates
Submission Portal Open: April 1st, 2026
Paper Submission Deadline: May 15th, 2026
Notification of Acceptance: July 31st, 2026
Please email your inquiry related to paper submissions to [email protected]