Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem
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We present a randomized iterative algorithm that exponentially converges in the mean square to the minimum l(2)-norm least squares solution of a given linear system of equations. The expected number of arithmetic operations required to obtain an estimate o ...
Society for Industrial and Applied Mathematics2013
We introduce a new wavelet-based method for the implementation of Total-Variation-type denoising. The data term is least-squares, while the regularization term is gradient-based. The particularity of our method is to exploit a link between the discrete gra ...
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Association for Research in Vision and Ophthalmology2013
We evaluated a laser-based noncontacting method to measure the elastic anisotropy of horizontal shale cores. Whereas conventional transducer data contained an ambiguity between phase and group velocity measurements, small laser source and receiver footprin ...
Unconstrained Least-Squares minimization is a well-studied problem. For example, the Levenberg-Marquardt is extremely effective and numerous implementations are readily available. These algorithms are, however, not designed to perform least-squares minimiz ...
A high-speed and hardware-only algorithm using a center of mass method has been proposed for singledetector fluorescence lifetime sensing applications. This algorithm is now implemented on a field programmable gate array to provide fast lifetime estimates ...
The identification of reliable reaction and mass-transfer rates is important for building first-principles models of gas-liquid reaction systems. The identification of these rates involves the determination of a model structure (reaction stoichiometry, rat ...
A new approach for gradient estimation in the context of real-time optimization under uncertainty is proposed in this paper. While this estimation problem is often a difficult one, it is shown that it can be simplified significantly if an assumption on the ...
In this correspondence, we provide a transient analysis of an affinely constrained mixture method that adaptively combines the outputs of adaptive filters running in parallel on the same task. The affinely constrained mixture is adapted using a stochastic ...