The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We study accelerated dual gradient-based methods for image denoising/deblurring problems based on the total variation (TV) model. For the TV-based denoising problem, combining the dual approach and Nesterov's fast gradient projection (FGP) method has been found effective. The corresponding denoising method minimizes the dual function with FGP's optimal rate O(1/k2) where k denotes the number of iterations,...
First-order methods are used widely for large scale optimization problems in signal/image processing and machine learning, because their computation depends mildly on the problem dimension. Nesterov's fast gradient method (FGM) has the optimal convergence rate among first-order methods for smooth convex minimization; its extension to non-smooth case, the fast iterative shrinkage-thresholding algorithm...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.