The 32nd MLSP workshop, an annual event organized by the IEEE Signal Processing Society MLSP Technical Committee, will present the most recent and exciting advances in machine learning for signal processing through keynote talks, tutorials, special and regular single-track sessions, and demonstration sessions. Prospective authors are invited to submit papers on relevant algorithms and applications including, but not limited to:

• Cognitive information learning
• Deep learning techniques
• Dictionary learning
• Graphical and kernel methods
• Matrix factorization/completion
• Independent component analysis
• Information-theoretic learning
• Learning theory and algorithms
• Learning form multimodal data

• ML over wireless networks
• Applications in music and audio
• Pattern recognition and classification
• Subspace and manifold learning
• Sequential learning
• Distributed/Federated learning
• Reinforcement learning
• Transfer learning
• Self/semi-supervised learning

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.