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