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We propose a convergence analysis of accelerated forward-backward splitting methods for composite function minimization, when the proximity operator is not available in closed form, and can only be computed up to a certain precision. We prove that the 1/k( ...
This study investigates the use of interface Peclet number P = w/(D-l/V-tip), to determine the interface width (w) used in phase-field simulations, where D-l is the liquid diffusivity and V-tip is the tip velocity. The maximum simulation interface width (w ...
Many rivers worldwide show converging sections where a characteristic limiting front for vegetation establishment on gravel bars is observed. An important conceptual model was advanced in 2006 by Gurnell and Petts, who demonstrated that for the convergent ...
Spatially coupled low-density parity-check codes show an outstanding performance under the low-complexity belief propagation (BP) decoding algorithm. They exhibit a peculiar convergence phenomenon above the BP threshold of the underlying non-coupled ensemb ...
We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Theoretical results about the co ...
Recent results on the convergence of a Galerkin projection method for the Sylvester equation are extended to more general linear systems with tensor product structure. In the Hermitian positive definite case, explicit convergence bounds are derived for Gal ...
Society for Industrial and Applied Mathematics2013
We present an empirical study that illustrates the potential of dual eye-tracking to detect successful understanding and social processes during pair programming. The gaze of forty pairs of programmers was recorded during a program understanding task. An a ...
In this work we consider the problem of approximating the statistics of a given Quantity of Interest (QoI) that depends on the solution of a linear elliptic PDE defined over a random domain parameterized by N random variables. The elliptic problem is remap ...
Many applications in machine learning require optimizing unknown functions defined over a high-dimensional space from noisy samples that are expensive to obtain. We address this notoriously hard challenge, under the assumptions that the function varies onl ...
We analyze the stochastic initial-boundary value problem for the elastic wave equation with random coefficients and deterministic data. We propose a stochastic collocation method for computing statistical moments of the solution or statistics of some given ...
