Description:
Explore methods for $\ell_p$-$\ell_q$ minimization and their applications in image restoration and regression with nonconvex loss and penalty in this one-hour virtual seminar. Delve into minimization problems with objective functions combining fidelity and regularization terms determined by p-norms and q-norms, respectively, where 0
Methods for L_p-L_q Minimization in Image Restoration and Regression - SIAM-IS Seminar
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#Computer Science
#Artificial Intelligence
#Computer Vision
#Image Processing
#Image Restoration
#Engineering
#Electrical Engineering
#Signal Processing
#Mathematics
#Statistics & Probability
#Statistical Modeling
#Regression Analysis
#Applied Mathematics
#Numerical Methods
#Machine Learning
#Nonconvex Optimization
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