About this Research Topic
This Research Topic will cover mathematical topics related to low-rank modeling and sparse modeling crucial to the advancement of data science including, but not limited to:
• Robust low-rank/sparse modeling for data analysis
• Robust principal component analysis (RPCA), Online algorithms for RPCA, etc.
• Relations between sparse/low-rank modeling and deep learning
• Robust sparse/low-rank subspace discovery
• Tensor data versions of the above problems
• Fast solvers for the non-smooth and nonconvex models
• Applications to robust image/video processing (e.g., denoising and restoration) and recognition, etc.
Keywords: Low-rank modeling, sparse modeling, machine learning, computer vision, image processing, video processing, data science, mathematics
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