IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2024

The IEEE MLSP 2024 will solicit papers that are devoted to the most recent and exciting advances in machine learning for signal processing. To be specific, we have come up with the following tentative technical tracks to give a better idea of the topics to be covered in MLSP 2024:

• Advanced optimisation methods
• Bayesian and probabilistic inference
• Data analytics 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
• Pattern recognition and classification
• Subspace and manifold learning
• Virtual and augmented reality data processing

Submission of papers: Prospective 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.