Common Contracts
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Distribution AgreementDistribution Agreement • April 4th, 2019
where Σˆb is the noise covariance matrix related to ˆbi and (xi)ml is the maximum likelihood estimator to the i-th row of X. Even though this model is based on the maximum likelihood estimator, we can compute the solution corresponding to each row slice one at a time, and sum when they all are computed. Each small- sized problem does not depend on others, so these can also be solved in parallel. For the second step, we need to quantify the noise propagation and solve a least squares optimization problem under bound constraints. To solve the corresponding optimization problem, we use FISTA with projections onto the boundary to obtain faster convergence and higher accuracy. Instead of using the two-step method, we can build a coupled optimization problem based on (1.5) and solve W directly. Numerical experiments show that the expense is lower and reconstructed images are of higher quality using the two-step framework compared with the coupled method.
