We introduce a "generalized small inverse problem (GSIP)" and present an algorithm for solving this problem. GSIP is formulated as finding small solutions of f(x0, x1, . ...
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
We consider the methods xδ n+1 = xδ n − gαn (F (xδ n)∗F (xδ n))F (xδ n)∗(F (xδ n)− yδ) for solving nonlinear ill-posed inverse problems F (x) = y using the only ava...
— We describe a stochastic optimization method that can be used to solve inverse problems in epidemic modelling. Although in general it cannot be expected that these inverse prob...
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known. Similarly as in [5],...