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.
A new deconvolution algorithm based on orthogonal projections onto the hyperplanes and the epigraph set of a convex cost function is presented. In this algorithm, the convex sets corresponding to the cost function are defined by increasing the dimension of the minimization problem by one. The Filtered Variation (FV) function is used as the convex cost function in this algorithm. Since the FV cost...
Recently, there have been growing interests in solving distributed consensus optimization problems over directed networks that consist of multiple agents. In this paper, we develop a first-order (gradient-based) algorithm, referred to as Push-DIGing, for this class of problems. To run Push-DIGing, each agent in the network only needs to know its own out-degree and employs a fixed step-size. Under...
We introduce the distributed Broyden-Fletcher-Goldfarb-Shanno (D-BFGS) method as an asynchronous decentralized variation of the BFGS quasi-Newton method for solving consensus optimization problems on a penalty function in the primal domain. The D-BFGS method is of interest in problems that are not well conditioned and in which second order information is not readily available, making decentralized...
We address for the first time the question of how networked agents can collaboratively fit a Morozov-regularized linear model when each agent knows a summand of the regression data. This question generalizes previously studied data-splitting scenarios, which require that the data be partitioned among the agents. To answer the question, we introduce a class of network-structured problems, which contains...
Performing inference on the Lie group of diffeomorphisms of Euclidean space has many applications, including computer vision, computational anatomy, and density estimation. Computational tools to find such diffeomorphisms typically involve dynamical systems, and computational fluid mechanics. We here consider the problem where we are given IID samples from a distribution P and want to learn a diffeomorphism...
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.