The 23rd MLSP workshop in the series of workshops 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 as well as special and regular single-track sessions. Prospective
authors are invited to submit papers on relevant algorithms and applications
including, but not limited to:
• Learning theory and techniques
• Graphical models and kernel methods
• Data-driven adaptive systems and models
• Pattern recognition and classification
• Distributed, Bayesian, subspace/manifold and sparsity-aware learning
• Multiset data analysis and multimodal data fusion
• Perceptual signal processing in audio, image and video
• Cognitive information processing
• Applications, including:
• Speech, audio and video
• Music processing
• Biomedical imaging
• Communications
• Bioinformatics
• Computational genomics
• Social networks
• Biometrics
• Energy and smart grid