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. The workshop will be held in a physical manner or a hybrid manner, depending on the global pandemic situation. 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